diff --git a/.github/ISSUE_TEMPLATE/bug-report.md b/.github/ISSUE_TEMPLATE/bug-report.md
new file mode 100755
index 0000000..5a3baa2
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/bug-report.md
@@ -0,0 +1,8 @@
+---
+name: "🐛 Bug Report"
+about: Create a report to help us improve
+title: ''
+labels: bug
+assignees: ''
+
+---
diff --git a/.github/ISSUE_TEMPLATE/feature-request.md b/.github/ISSUE_TEMPLATE/feature-request.md
new file mode 100755
index 0000000..972de88
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/feature-request.md
@@ -0,0 +1,8 @@
+---
+name: "🚀 Feature Request"
+about: Suggest an idea for this project
+title: ''
+labels: enhancement
+assignees: ''
+
+---
diff --git a/.github/ISSUE_TEMPLATE/question.md b/.github/ISSUE_TEMPLATE/question.md
new file mode 100755
index 0000000..2c22aea
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/question.md
@@ -0,0 +1,13 @@
+---
+name: "❓Question"
+about: Ask a general question
+title: ''
+labels: question
+assignees: ''
+
+---
+
+## ❔Question
+
+
+## Additional context
diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md
new file mode 100644
index 0000000..0af54de
--- /dev/null
+++ b/.github/PULL_REQUEST_TEMPLATE.md
@@ -0,0 +1,13 @@
+### Description
+
+This PR ...
+
+### Checklist
+
+- [ ] Linked issues (if existing)
+- [ ] Amended changelog.md for large changes (and added myself there as contributor)
+- [ ] Added/modified tests
+- [ ] Used pre-commit hooks when committing to ensure that code is compliant with hooks. Install hooks with `pre-commit install`.
+ To run hooks independent of commit, execute `pre-commit run --all-files`
+
+Thank you for joining. Have fun coding!
diff --git a/.github/workflows/codeql-analysis.yml b/.github/workflows/codeql-analysis.yml
new file mode 100644
index 0000000..f16fcfb
--- /dev/null
+++ b/.github/workflows/codeql-analysis.yml
@@ -0,0 +1,52 @@
+# This action runs GitHub's industry-leading static analysis engine, CodeQL, against a repository's source code to find security vulnerabilities.
+# https://github.com/github/codeql-action
+
+name: "CodeQL"
+
+on:
+ schedule:
+ - cron: '0 0 27 * *' # Runs at 00:00 UTC on the 27th of every month
+
+jobs:
+ analyze:
+ name: Analyze
+ runs-on: ubuntu-latest
+
+ strategy:
+ fail-fast: false
+ matrix:
+ language: ['python']
+ # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python' ]
+
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v3
+
+ # Initializes the CodeQL tools for scanning.
+ - name: Initialize CodeQL
+ uses: github/codeql-action/init@v2
+ with:
+ languages: ${{ matrix.language }}
+ # If you wish to specify custom queries, you can do so here or in a config file.
+ # By default, queries listed here will override any specified in a config file.
+ # Prefix the list here with "+" to use these queries and those in the config file.
+ # queries: ./path/to/local/query, your-org/your-repo/queries@main
+
+ # Autobuild attempts to build any compiled languages (C/C++, C#, or Java).
+ # If this step fails, then you should remove it and run the build manually (see below)
+ - name: Autobuild
+ uses: github/codeql-action/autobuild@v2
+
+ # ℹ️ Command-line programs to run using the OS shell.
+ # 📚 https://git.io/JvXDl
+
+ # ✏️ If the Autobuild fails above, remove it and uncomment the following three lines
+ # and modify them (or add more) to build your code if your project
+ # uses a compiled language
+
+ #- run: |
+ # make bootstrap
+ # make release
+
+ - name: Perform CodeQL Analysis
+ uses: github/codeql-action/analyze@v2
diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
new file mode 100644
index 0000000..8acd81b
--- /dev/null
+++ b/.github/workflows/lint.yml
@@ -0,0 +1,70 @@
+name: Lint
+
+on:
+ push:
+ branches: [master, main, dev]
+ pull_request:
+ branches: [master, main]
+
+jobs:
+ linter-black:
+ name: Check code formatting with Black
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout
+ uses: actions/checkout@v2
+ - name: Set up Python 3.8
+ uses: actions/setup-python@v2
+ with:
+ python-version: 3.8
+ - name: Install Black
+ run: pip install black[jupyter]
+ - name: Run Black
+ run: black --check .
+
+ imports-check-isort:
+ name: Check valid import formatting with isort
+ runs-on: ubuntu-latest
+ steps:
+ - name: Checkout
+ uses: actions/checkout@v2
+ - name: Set up Python 3.8
+ uses: actions/setup-python@v2
+ with:
+ python-version: 3.8
+ - name: Install isort
+ run: pip install isort==5.6.4
+ - name: Run isort
+ run: isort --check-only --diff .
+
+ linter-flake8:
+ name: Check valid formatting with flake8
+ runs-on: ubuntu-latest
+ timeout-minutes: 10
+ steps:
+ - name: Checkout
+ uses: actions/checkout@v2
+ - uses: actions/setup-python@v2
+ with:
+ python-version: 3.8
+
+ - name: Install dependencies
+ run: pip install flake8==3.9.2
+ - name: Run checks
+ run: flake8
+
+ pre-commit-hooks:
+ name: Check that pre-commit hooks pass
+ runs-on: ubuntu-latest
+ timeout-minutes: 10
+ steps:
+ - name: Checkout
+ uses: actions/checkout@v2
+ - uses: actions/setup-python@v2
+ with:
+ python-version: 3.8
+ - name: Install dependencies
+ run: pip install pre-commit
+
+ - name: Run checks
+ run: pre-commit run --all-files
diff --git a/.github/workflows/pypi_release.yml b/.github/workflows/pypi_release.yml
new file mode 100644
index 0000000..a366f6c
--- /dev/null
+++ b/.github/workflows/pypi_release.yml
@@ -0,0 +1,39 @@
+# This workflows will upload a Python Package using Twine when a release is created
+# For more information see: https://help.github.com/en/actions/language-and-framework-guides/using-python-with-github-actions#publishing-to-package-registries
+
+name: PyPi Release
+
+on:
+ push:
+ branches: [main]
+ release:
+ types: [created]
+
+jobs:
+ deploy:
+ runs-on: ubuntu-latest
+
+ steps:
+ - uses: actions/checkout@v2
+ - name: Set up Python
+ uses: actions/setup-python@v2
+ with:
+ python-version: '3.8'
+
+ - name: Install poetry
+ shell: bash
+ run: |
+ curl -sSL https://install.python-poetry.org | python3 -
+ python -m pip install poetry-dynamic-versioning[plugin]
+
+ - name: Set poetry path variable
+ run: echo "/Users/runner/.local/bin" >> $GITHUB_PATH
+
+ - name: Build
+ run: |
+ poetry build
+
+ - name: Publish distribution 📦 to PyPI
+ if: startsWith(github.event.ref, 'refs/tags') || github.event_name == 'release'
+ run: |
+ poetry publish --username "${{ secrets.PYPI_USERNAME }}" --password "${{ secrets.PYPI_PASSWORD }}"
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
new file mode 100644
index 0000000..b78dac0
--- /dev/null
+++ b/.github/workflows/test.yml
@@ -0,0 +1,125 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Test
+
+on:
+ push:
+ branches: [master, main, dev]
+ pull_request:
+ branches: [master, main, dev]
+
+jobs:
+ build:
+ runs-on: ${{ matrix.os }}
+ strategy:
+ matrix:
+ os: [ubuntu-latest, macOS-latest] # add windows-2019 when poetry allows installation with `-f` flag
+ python-version: [3.8, 3.9] # python 3.9 is not supported by all dependencies yet
+
+ steps:
+ - uses: actions/checkout@v2
+
+ - name: Set up Python ${{ matrix.python-version }}
+ uses: actions/setup-python@v2
+ with:
+ python-version: ${{ matrix.python-version }}
+
+ - name: Get full Python version
+ id: full-python-version
+ shell: bash
+ run: echo ::set-output name=version::$(python -c "import sys; print('-'.join(str(v) for v in sys.version_info))")
+
+ - name: Install poetry
+ shell: bash
+ run: |
+ curl -sSL https://install.python-poetry.org | python3 -
+ - name: Set poetry path variable
+ run: echo "/Users/runner/.local/bin" >> $GITHUB_PATH
+
+ - name: Configure poetry
+ shell: bash
+ run: poetry config virtualenvs.in-project true
+
+ - name: Set up cache
+ uses: actions/cache@v2
+ id: cache
+ with:
+ path: .venv
+ key: venv-${{ runner.os }}-${{ steps.full-python-version.outputs.version }}-${{ hashFiles('**/poetry.lock') }}
+
+ - name: Ensure cache is healthy
+ if: steps.cache.outputs.cache-hit == 'true'
+ shell: bash
+ run: poetry run pip --version >/dev/null 2>&1 || rm -rf .venv
+
+ - name: Upgrade pip
+ shell: bash
+ run: poetry run python -m pip install pip -U
+
+ - name: Install dependencies
+ shell: bash
+ run: poetry install --no-interaction --no-root
+
+ - name: Run unittest
+ shell: bash
+ run: poetry run coverage run -m unittest discover -s ./tests -p 'test_*.py'
+
+ - name: Statistics
+ if: success()
+ run: |
+ poetry run coverage report -i
+ poetry run coverage xml -i
+
+ - name: Upload coverage to Codecov
+ uses: codecov/codecov-action@v3
+ if: always()
+ continue-on-error: true
+ with:
+ token: ${{ secrets.CODECOV_TOKEN }}
+ file: coverage.xml
+ flags: cpu, unittest
+ name: CPU-coverage
+ fail_ci_if_error: false
+
+ docs:
+ name: Test docs build
+ runs-on: ubuntu-latest
+
+ steps:
+ - name: Check out Git repository
+ uses: actions/checkout@v2
+
+ - name: Set up Python
+ uses: actions/setup-python@v1
+ with:
+ python-version: 3.8
+
+ - name: Cache pip
+ uses: actions/cache@v2
+ with:
+ path: ~/.cache/pip
+ key: ${{ runner.os }}-pip-${{ hashFiles('docs/requirements_docs.txt') }}
+ restore-keys: |
+ ${{ runner.os }}-pip-
+
+ - name: Install dependencies
+ run: |
+ sudo apt-get update && sudo apt-get install -y pandoc
+ python -m pip install --upgrade pip
+ pip install -r docs/requirements_docs.txt
+ shell: bash
+
+ - name: Build sphinx documentation
+ run: |
+ cd docs
+ make clean
+ make html --debug --jobs 2 SPHINXOPTS="-W"
+
+ - name: Upload built docs
+ uses: actions/upload-artifact@v2
+ with:
+ name: docs-results-${{ runner.os }}-${{ matrix.python-version }}-${{ matrix.requires }}
+ path: docs/build/html/
+ # Use always() to always run this step to publish test results when there are test failures
+ if: success()
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..569e40e
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,92 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# Sphinx documentation
+docs/_build/
+docs/source/api/
+docs/source/CHANGELOG.md
+
+# mkdocs documentation
+/site
+
+# pycharm
+.idea
+
+# vscode
+.vscode
+
+# checkpoints
+*.ckpt
+*.pkl
+.DS_Store
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# yuetan
+**/nohup.out
+/reference/
+/data/
+/weights/
+/reference/jobshoppro/*
+/business/*
+/examples/*.xlsx
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..ae55273
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,29 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+ - repo: https://github.com/pre-commit/pre-commit-hooks
+ rev: v4.1.0
+ hooks:
+ - id: trailing-whitespace
+ - id: end-of-file-fixer
+ - id: check-yaml
+ - id: check-ast
+ - repo: https://github.com/PyCQA/flake8
+ rev: "3.9.2"
+ hooks:
+ - id: flake8
+ - repo: https://github.com/pre-commit/mirrors-isort
+ rev: v5.10.1
+ hooks:
+ - id: isort
+ - repo: https://github.com/psf/black
+ rev: 22.3.0
+ hooks:
+ - id: black
+ - repo: https://github.com/nbQA-dev/nbQA
+ rev: 1.2.3
+ hooks:
+ - id: nbqa-black
+ - id: nbqa-isort
+ - id: nbqa-flake8
+ - id: nbqa-check-ast
diff --git a/.readthedocs.yml b/.readthedocs.yml
new file mode 100644
index 0000000..3a16e74
--- /dev/null
+++ b/.readthedocs.yml
@@ -0,0 +1,26 @@
+# .readthedocs.yml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Build documentation in the docs/ directory with Sphinx
+# reference: https://docs.readthedocs.io/en/stable/config-file/v2.html#sphinx
+sphinx:
+ configuration: docs/source/conf.py
+ fail_on_warning: false
+
+# Build documentation with MkDocs
+#mkdocs:
+# configuration: mkdocs.yml
+
+# Optionally build your docs in additional formats such as PDF and ePub
+formats:
+ - htmlzip
+
+# Optionally set the version of Python and requirements required to build your docs
+python:
+ version: 3.8
+ install:
+ - requirements: docs/requirements_docs.txt
diff --git a/CHANGELOG.md b/CHANGELOG.md
new file mode 100644
index 0000000..4eb3502
--- /dev/null
+++ b/CHANGELOG.md
@@ -0,0 +1,18 @@
+# Release notes
+
+## v0.0.1 Initial release (15/10/2022)
+
+### Added
+- solver support
+ - dispatching rules
+ - spt
+ - fifo
+ - edd
+ - forward scheduling
+ - backward scheduling
+ - meta heuristics
+ - local search
+ - genetic
+
+### Contributor
+- LongxingTan
diff --git a/LICENSE b/LICENSE
new file mode 100755
index 0000000..e9f1ff4
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,201 @@
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
+ "License" shall mean the terms and conditions for use, reproduction,
+ and distribution as defined by Sections 1 through 9 of this document.
+
+ "Licensor" shall mean the copyright owner or entity authorized by
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+
+ "Legal Entity" shall mean the union of the acting entity and all
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+ "You" (or "Your") shall mean an individual or Legal Entity
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+ "Work" shall mean the work of authorship, whether in Source or
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+ "Derivative Works" shall mean any work, whether in Source or Object
+ form, that is based on (or derived from) the Work and for which the
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+ "Contribution" shall mean any work of authorship, including
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+ "Contributor" shall mean Licensor and any individual or Legal Entity
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+ You may add Your own copyright statement to Your modifications and
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+ for use, reproduction, or distribution of Your modifications, or
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+ the conditions stated in this License.
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+ 5. Submission of Contributions. Unless You explicitly state otherwise,
+ any Contribution intentionally submitted for inclusion in the Work
+ by You to the Licensor shall be under the terms and conditions of
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+ Notwithstanding the above, nothing herein shall supersede or modify
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+ 6. Trademarks. This License does not grant permission to use the trade
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+ 8. Limitation of Liability. In no event and under no legal theory,
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+ of your accepting any such warranty or additional liability.
+
+ END OF TERMS AND CONDITIONS
+
+ APPENDIX: How to apply the Apache License to your work.
+
+ To apply the Apache License to your work, attach the following
+ boilerplate notice, with the fields enclosed by brackets "[]"
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+ file or class name and description of purpose be included on the
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+
+ Copyright [2023] [Longxing Tan]
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
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+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..5b96002
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,22 @@
+.PHONY: style test docs
+
+check_dirs := lekin examples tests
+
+# run checks on all files and potentially modifies some of them
+
+style:
+ black $(check_dirs)
+ isort $(check_dirs)
+ flake8 $(check_dirs)
+ pre-commit run --files $(check_dirs)
+
+# run tests for the library
+
+test:
+ python -m unittest
+
+# run tests for the docs
+
+docs:
+ make -C docs clean M=$(shell pwd)
+ make -C docs html M=$(shell pwd)
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..0e8d2a2
--- /dev/null
+++ b/README.md
@@ -0,0 +1,110 @@
+[license-image]: https://img.shields.io/badge/License-Apache%202.0-blue.svg
+[license-url]: https://opensource.org/licenses/Apache-2.0
+[pypi-image]: https://badge.fury.io/py/lekin.svg
+[pypi-url]: https://pypi.python.org/pypi/lekin
+[pepy-image]: https://pepy.tech/badge/lekin/month
+[pepy-url]: https://pepy.tech/project/lekin
+[build-image]: https://github.com/LongxingTan/python-lekin/actions/workflows/test.yml/badge.svg?branch=master
+[build-url]: https://github.com/LongxingTan/python-lekin/actions/workflows/test.yml?query=branch%3Amaster
+[lint-image]: https://github.com/LongxingTan/python-lekin/actions/workflows/lint.yml/badge.svg?branch=master
+[lint-url]: https://github.com/LongxingTan/python-lekin/actions/workflows/lint.yml?query=branch%3Amaster
+[docs-image]: https://readthedocs.org/projects/python-lekin/badge/?version=latest
+[docs-url]: https://python-lekin.readthedocs.io/en/latest/
+[coverage-image]: https://codecov.io/gh/longxingtan/python-lekin/branch/master/graph/badge.svg
+[coverage-url]: https://codecov.io/github/longxingtan/python-lekin?branch=master
+[codeql-image]: https://github.com/longxingtan/python-lekin/actions/workflows/codeql-analysis.yml/badge.svg
+[codeql-url]: https://github.com/longxingtan/python-lekin/actions/workflows/codeql-analysis.yml
+
+
+
+ python-lekin Text is not SVG - cannot display 13342 13332 GitHub
+
+
+**python-lekin** 是一个工厂智能排产调度工具，名字来源于`Lekin
+
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`
diff --git a/docs/source/rl.rst b/docs/source/rl.rst
new file mode 100644
index 0000000..2d0a87b
--- /dev/null
+++ b/docs/source/rl.rst
@@ -0,0 +1,2 @@
+rl
+=========
diff --git a/docs/source/rules.rst b/docs/source/rules.rst
new file mode 100644
index 0000000..ef8e91d
--- /dev/null
+++ b/docs/source/rules.rst
@@ -0,0 +1,71 @@
+Rules
+============
+
+分为rule-based、event-based、resource-based两种思路。
+
+SPT最短加工时间
+--------------------
+
+按任务所需工序时间长短，从短到长顺序排列.
+实现中，为保证工艺路径的先后约束关系，构造规则法通过循环的先后关系来保证满足约束。
+
+
+EDD最早预定交货期规则
+---------------------------
+
+按生产任务规定完成时刻（预定交货期）的先后，从先到后顺次排列
+
+SPT—EDD规则
+-----------------
+
+1）根据EDD规则安排D(max)为最小的方案。
+2）计算所有任务的总流程时间。
+3）查找方案中，预定交贷期（di）大于总流程时间的生产任务（不惟一），按SPT规则，将其中加工时间最大者排于最后。
+4）舍弃第3步能排定的最后任务者及其后序任务，回到第2步重复。
+
+
+关键路径法
+-------------
+
+关键路径是决定项目完成的最短时间，关键路径可能不止一条。
+
+其基本概念：
+最早开始时间 (Early start)
+最晚开始时间 (Late start)
+最早完成时间 (Early finish)
+最晚完成时间 (Late finish)
+松弛时间 (slack)
+
+正推方法确定每个任务的最早开始时间和最早完成时间，逆推方法确定每个任务的最晚完成时间和最晚开始时间。
+
+
+顺排
+-------------
+
+顺排和倒排，和其他规则启发式算法一样，一个工序集一个工序集的排。每排一个工序，工序job完成后，更新机器、job状态、后续job状态。
+顺排对下一道工序的约束是：最早开始时间
+
+.. code-block:: python
+ backward(operations, next_op_start_until, with_material_kitting_constraint, align_with_same_production_line, latest_start_time, latest_end_time) -> remaining_operations: list[operations],
+
+
+.. code-block:: python
+ assign_op(operation, is_critical, direction: str, ) -> chosen_resource, chosen_production_id, chosen_hours,
+
+在顺排中，排的比较紧密的资源往往就是瓶颈资源。
+
+倒排
+---------------
+
+每一个MO最早开始时间初始化：max(ESD, today)。确保开始时间不早于今天，或不早于资源日历最早开始时间
+倒排对下一道工序的约束是: 最晚结束时间
+
+倒排
+- 从业务上可以减少库存, just-in-time
+- 带来的结果是不连续
+- 影响连续排产的判断
+- 考虑物料齐套时，导致倒排可能需要一次次推倒重来
+
+
+.. code-block:: python
+ forward(operations, next_op_start_until, with_material_kitting_constraint, align_with_same_production_line, earliest_start_time, earliest_end_time)
diff --git a/examples/__init__.py b/examples/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/examples/data/k1.json b/examples/data/k1.json
new file mode 100644
index 0000000..1fdeef5
--- /dev/null
+++ b/examples/data/k1.json
@@ -0,0 +1,129 @@
+{
+ "itineraries": [
+ {
+ "itineraryName": "Itinerary 1",
+ "tasksList": [
+ {
+ "taskName": "Task 1",
+ "taskMachine": {
+ "machineName": "M1"
+ },
+ "taskDuration": 10.0
+ },
+ {
+ "taskName": "Task 2",
+ "taskMachine": {
+ "machineName": "M2"
+ },
+ "taskDuration": 5.0
+ },
+ {
+ "taskName": "Task 3",
+ "taskMachine": {
+ "machineName": "M3"
+ },
+ "taskDuration": 35.0
+ }
+ ]
+ },
+ {
+ "itineraryName": "Itinerary 2",
+ "tasksList": [
+ {
+ "taskName": "Task 1",
+ "taskMachine": {
+ "machineName": "M2"
+ },
+ "taskDuration": 25.0
+ },
+ {
+ "taskName": "Task 2",
+ "taskMachine": {
+ "machineName": "M1"
+ },
+ "taskDuration": 5.0
+ },
+ {
+ "taskName": "Task 3",
+ "taskMachine": {
+ "machineName": "M3"
+ },
+ "taskDuration": 30.0
+ },
+ {
+ "taskName": "Task 4",
+ "taskMachine": {
+ "machineName": "M4"
+ },
+ "taskDuration": 15.0
+ }
+ ]
+ },
+ {
+ "itineraryName": "Itinerary 3",
+ "tasksList": [
+ {
+ "taskName": "Task 1",
+ "taskMachine": {
+ "machineName": "M2"
+ },
+ "taskDuration": 5.0
+ },
+ {
+ "taskName": "Task 2",
+ "taskMachine": {
+ "machineName": "M4"
+ },
+ "taskDuration": 10.0
+ }
+ ]
+ },
+ {
+ "itineraryName": "Itinerary 4",
+ "tasksList": [
+ {
+ "taskName": "Task 1",
+ "taskMachine": {
+ "machineName": "M2"
+ },
+ "taskDuration": 15.0
+ },
+ {
+ "taskName": "Task 2",
+ "taskMachine": {
+ "machineName": "M3"
+ },
+ "taskDuration": 10.0
+ },
+ {
+ "taskName": "Task 3",
+ "taskMachine": {
+ "machineName": "M4"
+ },
+ "taskDuration": 20.0
+ },
+ {
+ "taskName": "Task 4",
+ "taskMachine": {
+ "machineName": "M1"
+ },
+ "taskDuration": 10.0
+ }
+ ]
+ }
+ ],
+ "machines": [
+ {
+ "machineName": "M1"
+ },
+ {
+ "machineName": "M2"
+ },
+ {
+ "machineName": "M3"
+ },
+ {
+ "machineName": "M4"
+ }
+ ]
+}
diff --git a/examples/genetic_example.py b/examples/genetic_example.py
new file mode 100644
index 0000000..e69de29
diff --git a/examples/rule_example.py b/examples/rule_example.py
new file mode 100644
index 0000000..46d0cb3
--- /dev/null
+++ b/examples/rule_example.py
@@ -0,0 +1,101 @@
+import json
+import logging
+
+from lekin.dashboard.gantt import get_scheduling_res_from_all_jobs, plot_gantt_chart
+from lekin.lekin_struct import (
+ Job,
+ JobCollector,
+ Operation,
+ OperationCollector,
+ Resource,
+ ResourceCollector,
+ Route,
+ RouteCollector,
+)
+from lekin.solver.construction_heuristics import BackwardScheduler, ForwardScheduler, LPSTScheduler, SPTScheduler
+
+logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.DEBUG)
+
+
+def prepare_data(file_path="./data/k1.json"):
+ with open(file_path, "r", encoding="utf8") as file: # read file from path
+ data = json.loads(file.read())
+
+ job_collector = JobCollector()
+ # operation_collector = OperationCollector()
+ route_collector = RouteCollector()
+ resource_collector = ResourceCollector()
+
+ if list(data.keys()) == ["itineraries", "machines"]:
+ resources = data["machines"] # is first level structure is correct, then split
+ routes = data["itineraries"]
+
+ # parse the resource
+ for re in resources:
+ re_name = re["machineName"]
+ re_id = int(re_name.replace("M", ""))
+ resource = Resource(resource_id=re_id, resource_name=re_name)
+ resource_collector.add_resource_dict({re_id: resource})
+ # print([i.resource_id for i in resource_collector.get_all_resources()])
+ # print(resource_collector.get_all_resources()[0].available_hours)
+
+ # parse the job and route
+ for ro in routes:
+ # ro_name = ro["itineraryName"]
+ ro_id = int(ro["itineraryName"].replace("Itinerary ", ""))
+ route = Route(route_id=ro_id)
+ operations_sequence = []
+ for ta in ro["tasksList"]:
+ op_name = ta["taskName"]
+ op_id = ta["taskName"].replace("Task ", "")
+
+ op_pt = ta["taskDuration"]
+
+ op_tm = []
+ if isinstance(ta["taskMachine"], list):
+ for re in ta["taskMachine"]:
+ re_name = re["machineName"]
+ re_id = int(re_name.replace("M", ""))
+ op_tm.append(resource_collector.get_resource_by_id(re_id))
+ else:
+ re_name = ta["taskMachine"]["machineName"]
+ re_id = int(re_name.replace("M", ""))
+ op_tm.append(resource_collector.get_resource_by_id(re_id))
+
+ operations_sequence.append(
+ Operation(
+ operation_id=op_id,
+ operation_name=op_name,
+ quantity=1,
+ processing_time=op_pt,
+ parent_job_id=ro_id, # route defines job here
+ available_resource=op_tm,
+ )
+ )
+
+ route.operations_sequence = operations_sequence
+ route_collector.add_route(route)
+
+ job_collector.add_job(Job(job_id=ro_id, assigned_route_id=ro_id))
+
+ # print(resources)
+ # print(routes)
+
+ return job_collector, resource_collector, route_collector
+
+
+def run_scheduling(job_collector, resource_collector, route_collector):
+ # scheduler = ForwardScheduler(job_collector, resource_collector, route_collector)
+ scheduler = BackwardScheduler(job_collector, resource_collector, route_collector)
+
+ scheduler.run()
+ return
+
+
+if __name__ == "__main__":
+ job_collector, resource_collector, route_collector = prepare_data(file_path="./data/k1.json")
+ run_scheduling(job_collector, resource_collector, route_collector)
+
+ scheduling_res = get_scheduling_res_from_all_jobs(job_collector)
+ print(scheduling_res)
+ plot_gantt_chart(job_collector, scheduling_res)
diff --git a/lekin/__init__.py b/lekin/__init__.py
new file mode 100644
index 0000000..a743725
--- /dev/null
+++ b/lekin/__init__.py
@@ -0,0 +1,12 @@
+from lekin.datasets.get_data import get_data
+
+# from lekin.lekin_struct.job import Job
+# from lekin.lekin_struct.machine import Machine
+# from lekin.lekin_struct.operation import Operation
+# from lekin.lekin_struct.route import Route
+from lekin.scheduler import Scheduler
+from lekin.solver.meta_heuristics import Heuristics
+
+__all__ = ["Job", "Machine", "Route", "Operation", "Scheduler", "get_data"]
+
+__version__ = "0.0.0"
diff --git a/lekin/dashboard/__init__.py b/lekin/dashboard/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/dashboard/gantt.py b/lekin/dashboard/gantt.py
new file mode 100644
index 0000000..c3caabc
--- /dev/null
+++ b/lekin/dashboard/gantt.py
@@ -0,0 +1,70 @@
+"""
+Gantt
+"""
+
+import logging
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+from matplotlib import ticker
+import matplotlib.patches as patches
+import matplotlib.pyplot as plt
+import pandas as pd
+
+logging.getLogger("matplotlib.font_manager").disabled = True
+
+
+def get_scheduling_res_from_all_jobs(job_collector):
+ ops = []
+ for job in job_collector.job_list:
+ ops += job.operations
+
+ scheduling_res = []
+ for op in ops:
+ scheduling_res.append(
+ [
+ op.operation_id,
+ op.parent_job_id,
+ op.quantity,
+ op.assigned_resource.resource_id,
+ min(op.assigned_hours),
+ max(op.assigned_hours),
+ ]
+ )
+ scheduling_res = pd.DataFrame(scheduling_res, columns=["Operation", "Job", "Quantity", "Resource", "Start", "End"])
+ scheduling_res["Duration"] = scheduling_res["End"] - scheduling_res["Start"] # + 1
+ return scheduling_res
+
+
+def plot_gantt_chart(job_collector, scheduling_res):
+ color_dict = job_collector.generate_color_list_for_jobs()
+
+ # gantt
+ resource_list = []
+ for resource, group in scheduling_res.groupby("Resource"):
+ resource_list.append(resource)
+ start_tuple = []
+ color_tuple = []
+ for _, op in group.iterrows():
+ start_tuple.append(op[["Start", "Duration"]].tolist())
+ color_tuple.append(color_dict.get(op["Job"]))
+
+ plt.gca().broken_barh(start_tuple, ((resource + 1) * 10, 9), facecolors=color_tuple)
+
+ # legend
+ legends_colors = []
+ for job in job_collector.job_list:
+ legends_colors.append(patches.Patch(color=color_dict.get(job.job_id), label=f"job{job.job_id}"))
+ plt.legend(handles=legends_colors, fontsize=8)
+
+ # resource tick
+ resources = resource_list # list(reversed(resource_list))
+ resource_ticks = [15]
+ for i in range(len(resources)):
+ resource_ticks.append(resource_ticks[i] + 10) # machine increase + 10
+ plt.yticks(resource_ticks[1:], resources)
+
+ plt.grid(True)
+ plt.xlabel("Time")
+ plt.ylabel("Resources")
+ plt.title("Gantt Chart - Scheduling Result")
+ plt.show()
diff --git a/lekin/dashboard/pages.py b/lekin/dashboard/pages.py
new file mode 100644
index 0000000..51f2925
--- /dev/null
+++ b/lekin/dashboard/pages.py
@@ -0,0 +1,3 @@
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+import streamlit as st
diff --git a/lekin/datasets/__init__.py b/lekin/datasets/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/datasets/check_data.py b/lekin/datasets/check_data.py
new file mode 100644
index 0000000..c1c8cab
--- /dev/null
+++ b/lekin/datasets/check_data.py
@@ -0,0 +1,15 @@
+"""Check the input job shop format and necessary information"""
+
+import logging
+
+
+def check_data(data):
+ if data.keys() != ["routes", "machines"]:
+ logging.error("key")
+
+ if len(data["machines"]) < 1:
+ logging.error("machine")
+ if len(data["routes"]) < 1:
+ logging.error("route")
+
+ return
diff --git a/lekin/datasets/get_data.py b/lekin/datasets/get_data.py
new file mode 100644
index 0000000..715ca63
--- /dev/null
+++ b/lekin/datasets/get_data.py
@@ -0,0 +1,13 @@
+"""Generate the example jobshoppro"""
+
+import json
+import logging
+
+
+def get_data(name):
+ # machine_list = []
+ # route_list = []
+ if name == "simple":
+ pass
+
+ return
diff --git a/lekin/datasets/parse_data.py b/lekin/datasets/parse_data.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/forecast/__init__.py b/lekin/forecast/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/lekin_struct/__init__.py b/lekin/lekin_struct/__init__.py
new file mode 100644
index 0000000..10496be
--- /dev/null
+++ b/lekin/lekin_struct/__init__.py
@@ -0,0 +1,15 @@
+"""
+https://gitee.com/EnCode/APS?_from=gitee_search#%E5%BB%BA%E6%A8%A1
+
+工厂：订单
+车间：工单
+班组：工序
+操作动作：动作
+
+"""
+
+from lekin.lekin_struct.job import Job, JobCollector # 成品需求
+from lekin.lekin_struct.operation import Operation, OperationCollector # 工序
+from lekin.lekin_struct.resource import Resource, ResourceCollector # 机器
+from lekin.lekin_struct.route import Route, RouteCollector
+from lekin.lekin_struct.timeslot import TimeSlot
diff --git a/lekin/lekin_struct/job.py b/lekin/lekin_struct/job.py
new file mode 100644
index 0000000..88667f8
--- /dev/null
+++ b/lekin/lekin_struct/job.py
@@ -0,0 +1,154 @@
+"""
+Struct Job/订单作业
+ - a job could finish one product while finished
+ - job/mo/operation/activity
+"""
+
+from datetime import datetime
+import random
+from typing import Any, Callable, Dict, List, Optional, Tuple
+
+from lekin.lekin_struct.operation import Operation
+
+random.seed(315)
+
+
+class Job(object):
+ def __init__(
+ self,
+ job_id: str,
+ priority: int = None,
+ quantity: int = None,
+ demand_date: datetime = None,
+ job_type: str = None,
+ earliest_start_time=None,
+ assigned_route_id=None,
+ assigned_bom_id=None,
+ **kwargs: Dict,
+ ) -> None:
+ self.job_id: str = job_id
+ self.priority: int = priority
+ self.demand_date: datetime = demand_date
+ self.quantity: int = quantity
+ self.job_type: str = job_type
+ self.earliest_start_time: datetime = earliest_start_time # Material constraint
+ # cached scheduling result until the whole job is finished
+ self.cached_scheduling: dict = {}
+ self.assigned_route_id: str = assigned_route_id # Route object assigned to this job
+ self.assigned_bom_id: str = assigned_bom_id
+ self.current_operation_index: int = 0 # Record the current processing operation
+ self._operations_sequence: List[Operation] = [] # List of Operation objects for this job
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def assign_route(self, route_id):
+ self.assigned_route_id = route_id
+
+ @property
+ def operations(self):
+ return self._operations_sequence
+
+ def ger_next_operation(self):
+ if self.current_operation_index < len(self._operations_sequence):
+ return self._operations_sequence[self.current_operation_index]
+ else:
+ return None
+
+ def assign_cached_scheduling(self):
+ """assign all cached scheduling officially while all ops are fine"""
+ pass
+
+ def clear_cached_scheduling(self, all, start, dir):
+ """clear the cached scheduling result"""
+ pass
+
+ @operations.setter
+ def operations(self, operations_sequence):
+ self._operations_sequence = operations_sequence
+
+ def __eq__(self, other):
+ return
+
+ def __hash__(self):
+ return
+
+ def __str__(self):
+ return f"{self.job_id}"
+
+
+class JobCollector:
+ def __init__(self):
+ self.job_list = [] # List to store Job objects
+ self.color_dict = dict() # List to store colors for job
+ self.index = -1
+ # self.route_list = []
+ # self.operation_list = []
+ # self.resource_list = []
+ # self.time_slot_list = []
+
+ def __iter__(self):
+ return self
+
+ def __next__(self):
+ self.index += 1
+ if self.index < len(self.job_list):
+ return self.job_list[self.index]
+ else:
+ raise StopIteration("Stop")
+
+ def add_job(self, job: Job) -> None:
+ self.job_list.append(job)
+
+ def get_job_by_id(self, job_id: str):
+ for job in self.job_list:
+ if job.job_id == job_id:
+ return job
+ return None
+
+ def sort_jobs(self, jobs):
+ # Custom sorting function based on priority and continuity
+ def custom_sort(job):
+ priority_weight = (job.priority, job.demand_date)
+ # continuity_weight = -self.calculate_gap_time(job)
+ return priority_weight # + continuity_weight
+
+ # jobs = sorted(jobs, key=custom_sort, reverse=True)
+ return [i[0] for i in sorted(enumerate(jobs), key=lambda x: custom_sort(x[1]), reverse=False)]
+
+ def get_schedule(self):
+ schedule = {}
+
+ for resource in self.resource_list:
+ scheduled_operations = []
+ for operation in self.operation_list:
+ if operation.resource == resource:
+ scheduled_operations.append({"operation_id": operation.id, "start_time": operation.start_time})
+
+ if scheduled_operations:
+ schedule[resource.id] = scheduled_operations
+
+ return schedule
+
+ def generate_color_list_for_jobs(self, pastel_factor=0.5):
+ for job in self.job_list:
+ max_distance = None
+ best_color = None
+ for i in range(0, 100):
+ color = [
+ (x + pastel_factor) / (1.0 + pastel_factor) for x in [random.uniform(0, 1.0) for i in [1, 2, 3]]
+ ]
+ if color not in self.color_dict.values():
+ best_color = color
+ break
+ else:
+ best_distance = min([self.color_distance(color, c) for c in self.color_dict.values()])
+ if not max_distance or best_distance > max_distance:
+ max_distance = best_distance
+ best_color = color
+ self.color_dict.update({job.job_id: best_color})
+ return self.color_dict
+
+ @staticmethod
+ def color_distance(c1, c2):
+ return sum([abs(x[0] - x[1]) for x in zip(c1, c2)])
diff --git a/lekin/lekin_struct/material.py b/lekin/lekin_struct/material.py
new file mode 100644
index 0000000..5501117
--- /dev/null
+++ b/lekin/lekin_struct/material.py
@@ -0,0 +1,7 @@
+"""
+material struct
+- 物料属于需求的属性，连续排产时根据物料进行判断
+"""
+
+a = 1
+print(f"Schedule Job {a}/{a} backwards, " f"Num of ops: {a}, " "Demand date {a}, " "Priority {a}, " "Material {a}")
diff --git a/lekin/lekin_struct/operation.py b/lekin/lekin_struct/operation.py
new file mode 100644
index 0000000..2979741
--- /dev/null
+++ b/lekin/lekin_struct/operation.py
@@ -0,0 +1,146 @@
+"""
+Operation Struct
+op: 单个工单或新增需求的某一道工序
+GroupOP: 单个需求或多个需求必须在一起的一道工序
+MaterialOP: 同一物料多个需求的一道工序
+"""
+
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+
+
+class Operation:
+ def __init__(
+ self,
+ operation_id: str,
+ operation_name: str,
+ quantity: int,
+ beat_time: Union[int, List[int], float, List[float]],
+ processing_time: Union[int, List[int], float, List[float]],
+ pre_time: float = 0, # setup times
+ post_time: float = 0,
+ lead_time: float = 0,
+ lag_time: float = 0,
+ route_constraint=None,
+ available_resource=None,
+ available_resource_priority=None,
+ parent_job_id=None,
+ prev_operation_ids=None,
+ next_operation_ids=None,
+ **kwargs,
+ ):
+ self.operation_id = operation_id
+ self.operation_name = operation_name
+ self.quantity = quantity
+ self.beat_time = beat_time
+ self.processing_time = processing_time
+ self.pre_time = pre_time
+ self.post_time = post_time
+ self.lead_time = lead_time
+ self.lag_time = lag_time
+ # self.demand_time = demand_time
+ self.route_constraint = route_constraint
+ self.available_resource = available_resource
+ self.available_resource_priority = available_resource_priority
+ self.parent_job_id = parent_job_id
+ self.prev_operation_ids = prev_operation_ids # predecessors
+ self.next_operation_ids = next_operation_ids # successors
+
+ self.earliest_start_time = None
+ self.latest_start_time = None
+ self.earliest_end_time = None
+ self.latest_end_time = None
+
+ self.statue = "none" # none -> waiting -> pending -> done
+ self.assigned_resource = None # Track the assigned resource
+ self.assigned_time_slot = None # Track the assigned time slot
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ # Add a method to calculate granularity metric based on processing time and available time slot
+ def calculate_granularity_metric(self, available_time_slot):
+ # Calculate the granularity metric based on processing time and available time slot
+ pass
+
+ def is_finished(self):
+ return self.assigned_resource is not None
+
+ def __str__(self):
+ return f"{self.operation_id}-{self.operation_name}"
+
+
+class JobOperations(object):
+ """Operations from same job"""
+ def __init__(self, operation_list):
+ pass
+
+ @property
+ def job(self):
+ return
+
+
+class MaterialOperation(object):
+ """
+ 排产时, MaterialOperation, JobOperation, Operation是三层抽象结构
+ resource.assigned_material_op = list[MaterialOperation]
+ """
+ def __init__(self, job_operation_list):
+ pass
+
+ @property
+ def material(self):
+ return
+
+
+class OperationCollector:
+ def __init__(self):
+ self.operation_list = [] # List to store Operation objects
+
+ def add_operation(self, operation):
+ self.operation_list.append(operation)
+
+ def get_operation_by_id(self, operation_id):
+ for operation in self.operation_list:
+ if operation.operation_id == operation_id:
+ return operation
+ return None
+
+ def get_operations_by_job_and_route(self, job_list, route_list):
+ assert len(job_list) == len(route_list)
+
+ for job, route in zip(job_list, route_list):
+ # Get the operations for the current job and route
+ # route = route_list[route_index]
+ job_operations = route.get_operations()
+
+ # Fill in the job_id for each operation
+ for i, operation in enumerate(job_operations):
+ if i > 0:
+ operation.parent_operation_id = job_operations[i - 1].operation_id
+ if i < len(job_operations) - 1:
+ operation.next_operation_id = job_operations[i + 1].operation_id
+
+ operation.job_id = job.job_id
+
+ # Extend the list of all operations with the current job's operations
+ self.operation_list.extend(job_operations)
+
+ # Assign the operations to the current job
+ job.operations = job_operations
+ return self.operation_list
+
+ # def get_operations_by_job_and_route(self, job_list, route_list):
+ # assert len(job_list) == len(route_list)
+ # operation_list = []
+ # for operation in self.operations:
+ # if operation.parent_operation_id is None and operation.route_id == route_id:
+ # # If the operation is the first operation in the route
+ # current_operation = operation
+ # while current_operation:
+ # if current_operation.job_id == job_id:
+ # job_operations.append(current_operation)
+ # next_operation_id = current_operation.next_operation_id
+ # current_operation = next(
+ # (op for op in self.operations if op.operation_id == next_operation_id), None
+ # )
+ # return job_operations
diff --git a/lekin/lekin_struct/relation.py b/lekin/lekin_struct/relation.py
new file mode 100644
index 0000000..113bb77
--- /dev/null
+++ b/lekin/lekin_struct/relation.py
@@ -0,0 +1,18 @@
+"""
+工序之间的关系（工业工程）
+ES: 前工序完成后，后工序开始
+ES-Split: 前工序分割后，后工序应在所有分割工作完成后开始
+SS: 前后工序可以同时开始。即进程的“异步”关系
+SS-Split: 前工序分割后，后工序和最后一个分割工作同时开始
+EE: 后工序制造时间（自定义制造时间短）小于前工序，前后工序一起结束
+EE-SS: 后工序制造时间（自定义制造时间长）大于前工序，后工序开始时间不能超过前工序开始时间，所以前后工序一起开始后，无法保证前后工序一起结束。
+EE-Split: 后工序制造时间和前分割工序时间长度进行比较
+"""
+
+
+class OpRelation(object):
+ def __init__(self) -> None:
+ pass
+
+ def calculate(self, type: str):
+ return
diff --git a/lekin/lekin_struct/resource.py b/lekin/lekin_struct/resource.py
new file mode 100644
index 0000000..0e517d1
--- /dev/null
+++ b/lekin/lekin_struct/resource.py
@@ -0,0 +1,265 @@
+"""
+Resource/Machine Struct
+"""
+
+import math
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+import numpy as np
+import pandas as pd
+
+from lekin.lekin_struct.timeslot import TimeSlot
+
+
+class Resource:
+ def __init__(self, resource_id, resource_name=None, max_tasks=1, **kwargs):
+ self.resource_id = resource_id
+ self.resource_name = resource_name
+ self.max_tasks = max_tasks # maximum task can be done in same time, capacity
+ self.tasks = {time_slot: None for time_slot in range(1, max_tasks + 1)}
+ self._available_timeslots = []
+ self._available_hours = []
+
+ self.assigned_operations = []
+ self.assigned_time_slots = []
+ self.assigned_hours = []
+ self.pending_list = [] # 临时缓冲区
+ self.changeover_number = None # number of times
+ self.changeover_time = None # total time costs
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def add_timeslot(self, start_time, end_time):
+ self._available_timeslots.append(TimeSlot(start_time, end_time))
+ self._available_hours += TimeSlot(start_time, end_time).hours
+
+ def add_available_hours(self, hours):
+ self._available_hours = hours
+
+ @property
+ def available_hours(self):
+ return self._available_hours
+
+ @available_hours.setter
+ def available_hours(self, available_hours):
+ self._available_hours = available_hours
+
+ def init_job_op_from_op(self):
+ """op-> job_op"""
+ pass
+
+ def init_material_op_from_group_op(self):
+ """group_op-> material_op"""
+ pass
+
+ def update_op_from_material_op(self):
+ """material_op -> op"""
+ pass
+
+ def get_available_timeslot_for_op(self, start=None, end=None, periods=None, freq="1H", forward=True):
+ self.update_continuous_empty_hours()
+ select_hours = [i for i in self.available_hours if i <= end]
+
+ assert len(self.available_hours) == len(self.continuous_empty_hours)
+ front_available = self.continuous_empty_hours[: len(select_hours)]
+
+ chosen_hours_index = self.find_last_index_larger(periods, front_available)
+
+ if not chosen_hours_index:
+ back_available = self.continuous_empty_hours[len(select_hours) :]
+ chosen_hours_index = self.find_first_index_larger(periods, back_available)
+
+ if chosen_hours_index:
+ chosen_hours = self.available_hours[int(chosen_hours_index - periods) : chosen_hours_index]
+ return chosen_hours
+ else:
+ return []
+
+ def get_earliest_available_time(self, duration=None, start=None):
+ if len(self.available_hours) > len(self.assigned_hours):
+ return min(set(self.available_hours).difference(set(self.assigned_hours)))
+ else:
+ return None
+
+ def get_latest_available_time(self, duration=None, end=None):
+ self.update_continuous_empty_hours()
+ return max([i + 1 for (i, v) in enumerate(self.continuous_empty_hours[:end]) if v >= duration])
+
+ def update_continuous_empty_hours(self):
+ if len(self.available_hours) != len(self._available_timeslots):
+ pass
+ if len(self.assigned_hours) != len(self.assigned_time_slots):
+ pass
+
+ # for hours_list in self.available_hours:
+ empty_hours = []
+ continuous_hours = 0
+
+ for hour in self.available_hours:
+ if hour in self.assigned_hours: # Hour is not available
+ continuous_hours = 0
+ else:
+ continuous_hours += 1
+ empty_hours.append(continuous_hours)
+ self.continuous_empty_hours = empty_hours
+
+ def find_first_index_larger(self, input_value, lists):
+ for j, value in enumerate(lists):
+ if value > input_value:
+ return j
+ return None # If no value is larger than the input
+
+ def find_last_index_larger(self, input_value, lists):
+ lists = lists[::-1]
+ for j, value in enumerate(lists):
+ if value > input_value:
+ return len(lists) - j
+ return None
+
+ def get_available_time_slots_within_time(self, start=None, end=None, periods=None, freq="1H", forward=True):
+ available_hours = []
+
+ # check_periods = pd.date_range(start=start, end=end, periods=periods, freq=freq)
+ # if not forward:
+ # check_periods = check_periods[::-1]
+ # occupied_periods = [i.hours for i in self.assigned_time_slot]
+ # for period in check_periods:
+ # if period not in occupied_periods:
+ # available_hours.append(period)
+ # else: # considering the continuous assignment
+ # break
+
+ # all_available_end_time = [slot.end_time for slot in self.available_timeslots]
+ # just_in_time_end_time_slot = max([i for i in all_available_end_time if i <= end])
+ if forward:
+ selected_time_slot = [i for i in self.available_timeslots if i.start_time >= start]
+ else:
+ selected_time_slot = [i for i in self.available_timeslots if i.end_time <= end][::-1]
+
+ # print(just_in_time_end_time_slot)
+ # print([i.start_time for i in self.available_timeslots])
+ # print([i.end_time for i in self.available_timeslots])
+ # print(self.available_timeslots[0].hours)
+
+ left_periods = periods
+
+ for time_slot in selected_time_slot:
+ if left_periods <= 0:
+ break
+
+ if start and time_slot.start_time < start:
+ continue
+
+ if end and time_slot.start_time >= end:
+ break
+
+ # if forward:
+ # current_time = max(start, time_slot.start_time)
+ # else:
+ # current_time = min(end, time_slot.end_time)
+
+ if time_slot in self.assigned_time_slot:
+ break
+
+ if time_slot.duration_of_hours < left_periods:
+ available_hours += time_slot.hours
+ left_periods -= time_slot.duration_of_hours
+
+ else:
+ available_hours += time_slot.hours[-math.ceil(left_periods) :]
+ break
+ #
+ # print(left_periods, available_hours)
+
+ # for current_time in range(max(start, time_slot.start_time),
+ # min(end, time_slot.end_time - period) + 1):
+ # if all(self.is_available(current_time + offset, current_time +offset+1) for offset in range(periods)):
+ # available_hours.append(current_time)
+
+ return available_hours
+
+ def is_available(self, start_time, end_time):
+ for assigned_time_slot in self.assigned_time_slots:
+ if not (end_time <= assigned_time_slot.start_time or start_time >= assigned_time_slot.end_time):
+ return False
+ return True
+
+ def get_unoccupied_time_slots_within_time(self):
+ unoccupied_slots = []
+ prev_end_time = None
+ for time_slot in self.time_slots:
+ if not time_slot.is_occupied():
+ if prev_end_time:
+ # Check if there is a gap between unoccupied time slots
+ if time_slot.start_time > prev_end_time:
+ unoccupied_slots.append(TimeSlot(prev_end_time, time_slot.start_time))
+ unoccupied_slots.append(time_slot)
+ prev_end_time = time_slot.end_time
+ return unoccupied_slots
+
+ def merge_schedules(self):
+ # Sort timeslots based on start time
+ self.timeslots.sort(key=lambda x: x.start_time)
+
+ merged_slots = []
+ current_slot = None
+
+ for slot in self.timeslots:
+ if not current_slot:
+ current_slot = slot
+ else:
+ # If the current slot and the next slot overlap, merge them
+ if current_slot.end_time >= slot.start_time:
+ current_slot.end_time = max(current_slot.end_time, slot.end_time)
+ else:
+ merged_slots.append(current_slot)
+ current_slot = slot
+
+ if current_slot:
+ merged_slots.append(current_slot)
+
+ self.timeslots = merged_slots
+
+ def __hash__(self):
+ return hash(str(self))
+
+ def __str__(self):
+ return f"{self.resource_id}"
+
+ def __eq__(self, other):
+ return self.resource_id == other.resource_id
+
+ def __lt__(self, other):
+ return self.resource_id < other.resource_id
+
+
+class ResourceCollector:
+ def __init__(self):
+ self.resources = {}
+ self.index = -1
+
+ def __iter__(self):
+ return self
+
+ def __next__(self):
+ self.index += 1
+ if self.index < len(self.resources):
+ return list(self.resources.values())[self.index]
+ else:
+ raise StopIteration("Stop")
+
+ def add_resource_dict(self, resource: Resource):
+ self.resources.update({resource.resource_id: resource})
+
+ def get_resource_by_id(self, resource_id):
+ return self.resources.get(resource_id)
+
+ def get_all_resources(self):
+ return list(self.resources.values())
+
+ def get_unoccupied_time_slots(self):
+ unoccupied_slots = []
+ for resource in self.get_all_resources():
+ unoccupied_slots.extend(resource.get_unoccupied_time_slots())
+ return unoccupied_slots
diff --git a/lekin/lekin_struct/route.py b/lekin/lekin_struct/route.py
new file mode 100644
index 0000000..a4ea487
--- /dev/null
+++ b/lekin/lekin_struct/route.py
@@ -0,0 +1,59 @@
+"""
+Route map Struct
+"""
+
+from typing import Any, Callable, Dict, List, Optional, Tuple
+
+from lekin.lekin_struct.operation import Operation
+
+
+class Route:
+ def __init__(self, route_id, operations_sequence=None, available_resources=None, **kwargs):
+ self.route_id = route_id
+ self.operations_sequence = operations_sequence # List of Operation objects
+ self.available_resources = available_resources # List of Resource objects representing available machines,
+ # When assigning operations to resources, check for resource availability and consider resource capacities
+ self.available_time_slots = [] # List of time slots when machines are available
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def add_operation(self, operation: Operation):
+ self.operations_sequence.append(operation)
+
+ def get_operations(self) -> List[Operation]:
+ return self.operations_sequence
+
+ def add_resource(self, resource):
+ self.available_resources.append(resource)
+
+ def add_time_slot(self, time_slot):
+ self.available_time_slots.append(time_slot)
+
+ def __repr__(self):
+ return (
+ f"Route(route_id={self.route_id}, operation_ids={self.operations_sequence},"
+ f" resources_available={self.available_resources})"
+ )
+
+
+class RouteCollector:
+ def __init__(self):
+ self.routes = {}
+ self.index = -1
+
+ def __iter__(self):
+ return self
+
+ def __next__(self):
+ self.index += 1
+ if self.index < len(self.routes):
+ return list(self.routes.values())[self.index]
+ else:
+ raise StopIteration("Stop")
+
+ def add_route(self, route):
+ self.routes[route.route_id] = route
+
+ def get_route_by_id(self, route_id):
+ return self.routes.get(route_id, None)
diff --git a/lekin/lekin_struct/timeslot.py b/lekin/lekin_struct/timeslot.py
new file mode 100644
index 0000000..861f309
--- /dev/null
+++ b/lekin/lekin_struct/timeslot.py
@@ -0,0 +1,44 @@
+"""
+Calendar for resource Struct
+"""
+
+from datetime import datetime, timedelta
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+import pandas as pd
+
+
+class TimeSlot(object):
+ def __init__(self, start_time, end_time, **kwargs):
+ self.start_time = start_time
+ self.end_time = end_time
+ self.duration = end_time - start_time
+ self.assigned_operation = None
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def assign_operation(self, operation, processing_time):
+ self.assigned_operation = operation
+ self.end_time = self.start_time + timedelta(hours=processing_time)
+
+ def is_occupied(self):
+ return self.assigned_operation is not None
+
+ @property
+ def hours(self):
+ return pd.date_range(start=self.start_time, end=self.end_time, freq="1H").tolist()[:-1]
+
+ @property
+ def duration_of_hours(self):
+ return len(pd.date_range(start=self.start_time, end=self.end_time, freq="1H")) - 1
+
+ def overlaps_with(self, timeslot):
+ overlap_start = max(self.start_time, timeslot.start_time)
+ overlap_end = min(self.end_time, timeslot.end_time)
+
+ if overlap_start < overlap_end:
+ overlap_hours = (overlap_end - overlap_start).total_seconds() / 3600
+ return overlap_hours
+ else:
+ return 0
diff --git a/lekin/objective/__init__.py b/lekin/objective/__init__.py
new file mode 100644
index 0000000..428b4b1
--- /dev/null
+++ b/lekin/objective/__init__.py
@@ -0,0 +1,2 @@
+from lekin.objective.makespan import calculate_makespan
+from lekin.objective.tardiness import calculate_tardiness
diff --git a/lekin/objective/makespan.py b/lekin/objective/makespan.py
new file mode 100644
index 0000000..c354ece
--- /dev/null
+++ b/lekin/objective/makespan.py
@@ -0,0 +1,19 @@
+def calculate_makespan(job_collector):
+ for job in job_collector.job_list:
+ op = job.operations
+ job.makespan = op.assigned_hours[-1]
+
+ if job.demand_date is not None:
+ job.tardiness = job.makespan - job.demand_date
+ return
+
+
+def calculate_changeover_time(schedule_result, job_collector):
+ changeover_time = 0
+ for resource in job_collector.resources:
+ previous_end_time = 0
+ for operation in schedule_result:
+ if operation.resource == resource:
+ changeover_time += max(0, operation.start_time - previous_end_time)
+ previous_end_time = operation.end_time
+ return changeover_time
diff --git a/lekin/objective/tardiness.py b/lekin/objective/tardiness.py
new file mode 100644
index 0000000..785ea5e
--- /dev/null
+++ b/lekin/objective/tardiness.py
@@ -0,0 +1,30 @@
+"""Tardiness total/maximum/weighted"""
+
+
+def calculate_tardiness(schedule_result, job):
+ end_time = schedule_result[job.route.operations[-1]][1]
+ return max(0, end_time - job.demand_date)
+
+
+def calculate_total_tardiness(schedule_result, jobs):
+ total_tardiness = 0
+ for job in jobs:
+ total_tardiness += calculate_tardiness(schedule_result, job)
+ return total_tardiness
+
+
+def calculate_total_late_jobs(schedule_result, jobs):
+ total_late_jobs = 0
+ for job in jobs:
+ if calculate_tardiness(schedule_result, job) > 0:
+ total_late_jobs += 1
+ return total_late_jobs
+
+
+def calculate_total_late_time(schedule_result, jobs):
+ total_late_time = 0
+ for job in jobs:
+ tardiness = calculate_tardiness(schedule_result, job)
+ if tardiness > 0:
+ total_late_time += tardiness
+ return total_late_time
diff --git a/lekin/scheduler.py b/lekin/scheduler.py
new file mode 100644
index 0000000..4662266
--- /dev/null
+++ b/lekin/scheduler.py
@@ -0,0 +1,25 @@
+"""Flexible job shop scheduler
+Rescheduler due to inserted order or default machine
+"""
+
+from collections import OrderedDict
+import logging
+from typing import Any, Callable, Dict, List, Optional, Tuple
+
+from lekin.datasets.check_data import check_data
+
+
+class Scheduler(object):
+ def __init__(self, objective, solver, max_operations, **kwargs):
+ self.objective = objective
+ self.solver = solver
+ self.max_operations = max_operations
+
+ def run(self, jobs, machines):
+ self.solver.solve(jobs, machines)
+
+ def evaluate(self):
+ pass
+
+ def plot(self):
+ pass
diff --git a/lekin/solver/__init__.py b/lekin/solver/__init__.py
new file mode 100644
index 0000000..cd5f2f6
--- /dev/null
+++ b/lekin/solver/__init__.py
@@ -0,0 +1,363 @@
+"""
+交付
+连续
+均衡
+"""
+
+from datetime import datetime, timedelta
+import heapq
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+import pandas as pd
+
+from lekin.lekin_struct.operation import Operation
+
+
+class CTPSolver(object):
+ def __init__(self, optimizers=None):
+ self.optimizers = optimizers
+
+ def run(self, job_collector, route_list, resource_collector, operation_resource):
+ sorted_index = sort_jobs(job_collector.job_list)
+ job_list = [job_collector.job_list[i] for i in sorted_index]
+
+ for i, job in enumerate(job_list):
+ route_id = job.assigned_route_id
+ route = None
+ for r in route_list:
+ if r.route_id == route_id:
+ route = r
+ break
+ if not route:
+ print(f"Route with ID '{job.assigned_route_id}' not found for Job ID '{job.job_id}'. Skipping job.")
+ continue
+
+ operations_sequence = route.operations_sequence[::-1] # Reverse the operations in the route
+ print([i.operation_id for i in operations_sequence])
+
+ current_end_time = job.demand_date
+
+ for operation in operations_sequence:
+ job_id = job.job_id
+ operation_id = operation.operation_id
+
+ temp = operation_resource.loc[
+ (operation_resource["产品ID"] == job_id) & (operation_resource["工序ID"] == operation_id)
+ ]
+
+ operation.available_resource = [
+ resource_collector.get_resource_by_id(i) for i in temp["资源需求组合ID"].tolist()
+ ]
+ operation.processing_time = temp["任务加工时长"].tolist()
+ operation.quantity = job.quantity
+
+ print(
+ operation.operation_id,
+ operation.available_resource,
+ operation.processing_time,
+ operation.quantity,
+ current_end_time,
+ )
+
+ # 对于不同工序依赖进行更新 & calculate the time constraint
+ # Calculate earliest and latest start times based on demand time and route constraint
+ latest_end_time = current_end_time
+ if operation.next_operation_ids is not None:
+ pass
+ # get_operation_time_constraint()
+
+ resource, start_time, end_time = find_best_resource_and_timeslot_for_operation(
+ operation, latest_end_time=latest_end_time
+ )
+
+ def reschedule_operation(self, operation):
+ # TODO: Implement dynamic rescheduling logic here, considering conflicts with other operations,
+ # resource availability, and any other relevant constraints.
+ pass
+
+
+def sort_jobs(jobs):
+ # Custom sorting function based on priority and continuity
+ def custom_sort(job):
+ priority_weight = job.priority # You may adjust the weight based on your requirements
+ # continuity_weight = -self.calculate_gap_time(job)
+ return priority_weight # + continuity_weight
+
+ # jobs = sorted(jobs, key=custom_sort, reverse=True)
+ return [i[0] for i in sorted(enumerate(jobs), key=lambda x: custom_sort(x[1]), reverse=False)]
+
+
+def get_operation_time_constraint():
+ # calculate the earliest start time and latest end time
+ return
+
+
+def find_best_resource_and_timeslot_for_operation(
+ operation: Operation, earliest_start_time=None, latest_end_time=None, allowed_conflict=False
+):
+ # assign operation
+ resource_timeslots_pq: List = [] # Create a priority queue to store the possible resource-time slot pairs
+ available_resource = operation.available_resource
+ # if operation.required_resource_priority is not None:
+ # required_resource.sort() # Sort by resource priority
+
+ for i, resource in enumerate(available_resource):
+ # start_time = max(operation.prev_operation.end_time, earliest_start_time)
+ # end_time = min(start_time + operation.processing_time, latest_end_time)
+
+ resource_all_available_end_time = [slot.end_time for slot in resource.available_timeslots]
+ just_in_time_end_time_slot = max([i for i in resource_all_available_end_time if i <= latest_end_time])
+ print(latest_end_time, just_in_time_end_time_slot)
+
+ if hasattr(operation.beat_time, "__iter__"):
+ working_hours = (operation.beat_time[i] * operation.quantity) / 60
+
+ unoccupied_hours = resource.get_available_time_slots_within_time()
+ if unoccupied_hours >= working_hours:
+ # assign
+ pass
+ else:
+ pass
+
+ # required processing time and time slot
+
+ just_in_time_slot = find_time_slots(resource, operation, "just_in_time")
+ if just_in_time_slot:
+ evaluation_score = calculate_evaluation_score(operation, just_in_time_slot, resource)
+ heapq.heappush(resource_timeslots_pq, (evaluation_score, resource, just_in_time_slot))
+
+ # If no "just in time" time slot is found, search for available time slots in the past
+ if not resource_timeslots_pq:
+ past_time_slots = find_time_slots(resource, operation, "history")
+ for timeslot in past_time_slots:
+ evaluation_score = calculate_evaluation_score(operation, timeslot, resource)
+ heapq.heappush(resource_timeslots_pq, (evaluation_score, resource, timeslot))
+
+ # If still no suitable time slot is found, look for available time slots in the future
+ # if in future, all the next operation need to be rescheduling forwards
+ if not resource_timeslots_pq:
+ future_time_slots = find_time_slots(resource, operation, "future")
+ for timeslot in future_time_slots:
+ evaluation_score = calculate_evaluation_score(operation, timeslot, resource)
+ heapq.heappush(resource_timeslots_pq, (evaluation_score, resource, timeslot))
+
+ if resource_timeslots_pq:
+ _, chosen_resource, chosen_timeslot = heapq.heappop(resource_timeslots_pq)
+ operation.assigned_resource = chosen_resource
+ operation.assigned_timeslot = chosen_timeslot
+ resource.available_timeslots -= chosen_timeslot
+ return True
+
+
+def find_just_in_time_slots(resource, num_time_slots, duration_hours, job_demand_date):
+ available_slots = resource.get_available_time_slots()
+ just_in_time_slots = []
+
+ for slot in available_slots:
+ slot_end = slot + duration_hours
+ if slot_end <= job_demand_date:
+ just_in_time_slots.append(slot)
+ if len(just_in_time_slots) >= num_time_slots:
+ break
+
+ return just_in_time_slots
+
+
+def find_time_slots(resource, operation, time_slot_type, latest_end_time, working_hours):
+ # Find available time slots in the resource for the operation.
+ # The time_slot_type can be 'just_in_time', 'history', or 'future'.
+ end_time = [slot.end_time for slot in resource.time_slots]
+ time_slots = []
+ if time_slot_type == "just_in_time":
+ # Find a "just in time" time slot where the operation can finish just before the job's demand date.
+
+ resource_all_available_end_time = [slot.end_time for slot in resource.available_timeslots]
+ just_in_time_end_time_slot = max([i for i in resource_all_available_end_time if i <= latest_end_time])
+ unoccupied_hours = resource.get_available_time_slots_within_time(just_in_time_end_time_slot)
+ if unoccupied_hours >= working_hours:
+ duration_hours = 0
+ for slot in unoccupied_hours[::-1]:
+ time_slots.append(slot)
+ duration_hours += len(slot.hours)
+
+ if duration_hours >= working_hours:
+ break
+
+ elif time_slot_type == "history":
+ # Find available time slots in the past that allow the operation to finish before the demand date.
+ past_time_slots = []
+ for slot in resource.timeslots:
+ if slot.end_time <= end_time:
+ past_time_slots.append(slot)
+ return past_time_slots
+ elif time_slot_type == "future":
+ # Find available time slots in the future that allow the operation to finish before the demand date.
+ future_time_slots = []
+ for slot in resource.timeslots:
+ if slot.start_time >= end_time:
+ future_time_slots.append(slot)
+ return future_time_slots
+ else:
+ raise ValueError("Invalid time_slot_type. It should be 'just_in_time', 'history', or 'future'.")
+
+
+def calculate_evaluation_score(self, operation, timeslots, resource):
+ # Implement evaluation function here, consider factors like changeover time, priority, lead time, etc.
+ # The evaluation function should consider conflicts with other operations and
+ # prioritize the best resource and timeslot sequence
+ priority_score = operation.priority
+ changeover_score = self.calculate_total_changeover_score(operation, timeslots, resource)
+
+ return priority_score + changeover_score
+
+
+def calculate_conflicts_hours(resource, operation):
+ for op in resource.assigned_operation:
+ if operation.time_slot.overlaps_with(op.time_slot):
+ # Handle conflict: Apply resolution strategy
+ # adjust_start_times(operations[i], operations[j])
+ pass
+ return
+
+
+def calculate_delay_hours(operation):
+ pass
+
+
+def calculate_total_changeover_score(resource, operation, timeslots):
+ # Implement your total changeover calculation
+ # calculate the changeover time between the current operation and the previous one in the resource's task sequence
+
+ # Example: A simple total changeover calculation based on processing time of the previous operation
+ total_changeover_time = 0
+ if resource.assigned_operation:
+ previous_operation = resource.task_sequence[-1].operation
+ for timeslot in timeslots:
+ total_changeover_time += abs(previous_operation.processing_time - operation.processing_time)
+
+ return total_changeover_time
+
+
+class ConflictResolver:
+ def __init__(self, resources):
+ self.resources = resources
+
+ def merge_and_resolve(self):
+ # Merge backward and forward schedules
+ for resource in self.resources:
+ resource.merge_schedules()
+
+ # Resolve conflicts
+ for resource in self.resources:
+ self.resolve_conflicts(resource)
+
+ def resolve_conflicts(self, resource):
+ # Find overlapping operations on the same resource at the same time
+ overlapping_ops = self.find_overlapping_operations(resource)
+
+ # Resolve conflicts
+ for op1, op2 in overlapping_ops:
+ # Adjust the start or end time of operations to resolve conflicts
+ self.adjust_times_for_conflict(op1, op2)
+
+ def find_overlapping_operations(self, resource):
+ overlapping_ops = []
+ for time_slot in resource.schedules:
+ ops_in_timeslot = resource.schedules[time_slot]
+ if len(ops_in_timeslot) > 1:
+ # Multiple operations in the same time slot indicate a conflict
+ for i in range(len(ops_in_timeslot)):
+ for j in range(i + 1, len(ops_in_timeslot)):
+ overlapping_ops.append((ops_in_timeslot[i], ops_in_timeslot[j]))
+ return overlapping_ops
+
+ def adjust_times_for_conflict(self, op1, op2):
+ # Implement your logic to adjust the start or end time of operations
+ # based on your specific requirements and constraints.
+ # You can consider factors like priority, changeovers, lead times, etc.
+ # For example, you might want to adjust the end time of op1 or the start time of op2.
+ # Check if op2 starts before op1 ends
+ if op2.start_time < op1.end_time:
+ # Calculate the time difference between op2's start time and op1's end time
+ time_difference = op1.end_time - op2.start_time
+
+ # Update op2's start time to be after op1's end time
+ op2.start_time += time_difference
+
+ # Adjust the end time of the job if it exceeds the demand date
+ if op2.end_time > op2.job.demand_date:
+ op2.job.demand_date = op2.end_time
+
+ def resolve_conflicts2(self):
+ # Sort operations by their route requirements and processing time
+ self.operations.sort(key=lambda op: (op.route.priority, op.processing_time))
+
+ for operation in self.operations:
+ # Find a suitable time slot for the operation
+ suitable_time_slot = self.find_suitable_time_slot(operation)
+
+ if suitable_time_slot is not None:
+ # Assign the operation to the resource and time slot
+ operation.resource = suitable_time_slot.resource
+ operation.time_slot = suitable_time_slot
+
+ # Update resource's assigned operations
+ suitable_time_slot.resource.assign_operation(operation)
+
+ def find_suitable_time_slot(self, operation):
+ # Sort available time slots based on priority, earliest start time, and resource availability
+ available_time_slots = sorted(
+ self.resources,
+ key=lambda resource: (
+ resource.priority,
+ resource.get_earliest_start_time(),
+ resource.get_latest_end_time(),
+ ),
+ )
+
+ for time_slot in available_time_slots:
+ # Check if the resource's time slot is compatible with the operation's route
+ if time_slot.resource.is_compatible_route(operation.route):
+ # Check if there are any conflicts with other operations in the time slot
+ if not time_slot.has_conflicts(operation.processing_time):
+ return time_slot
+
+ return None # No suitable time slot found
+
+
+# --
+#
+# for start_index in range(len(resource.timeslots) - operation.required_time_slots + 1):
+# # Check if consecutive time slots can accommodate the entire operation
+# can_accommodate = True
+# for i in range(operation.required_time_slots):
+# timeslot = resource.timeslots[start_index + i]
+# if self.check_timeslot_conflict(resource, timeslot):
+# can_accommodate = False
+# break
+#
+# if can_accommodate:
+# end_index = start_index + operation.required_time_slots - 1
+# evaluation_score = self.calculate_evaluation_score(operation,
+# resource.timeslots[start_index:end_index + 1],
+# resource)
+# heappush(priority_queue, (evaluation_score, resource, resource.timeslots[start_index:end_index + 1]))
+#
+# if end_time >= start_time + processing_time:
+# delay_time = max(0, operation.job.demand_date - end_time)
+# changeover_time = self.calculate_changeover_time(last_operation, resource)
+# priority_score = delay_time + changeover_time + resource.priority
+# heapq.heappush(resource_timeslots, (priority_score, resource, start_time, end_time))
+#
+# while resource_timeslots:
+# _, resource, start_time, end_time = heapq.heappop(resource_timeslots)
+#
+# # Create a temporary timeslot for the operation
+# temp_timeslot = Timeslot(start_time, end_time)
+#
+# # Check if the time slot overlaps with any of the previous task's timeslots
+# if not self.check_timeslot_conflict(resource, temp_timeslot):
+# # Assign the operation to the current resource and timeslot
+# operation.assigned_resource = resource
+# operation.assigned_timeslot = temp_timeslot
+# return
diff --git a/lekin/solver/construction_heuristics/__init__.py b/lekin/solver/construction_heuristics/__init__.py
new file mode 100644
index 0000000..e2497db
--- /dev/null
+++ b/lekin/solver/construction_heuristics/__init__.py
@@ -0,0 +1,9 @@
+"""Dispatching rules"""
+
+from lekin.solver.construction_heuristics.atcs import ATCScheduler
+from lekin.solver.construction_heuristics.backward import BackwardScheduler
+from lekin.solver.construction_heuristics.forward import ForwardScheduler
+from lekin.solver.construction_heuristics.lpst import LPSTScheduler
+from lekin.solver.construction_heuristics.spt import SPTScheduler
+
+__all__ = [ATCScheduler, LPSTScheduler, SPTScheduler, ForwardScheduler, BackwardScheduler]
diff --git a/lekin/solver/construction_heuristics/atcs.py b/lekin/solver/construction_heuristics/atcs.py
new file mode 100644
index 0000000..171208c
--- /dev/null
+++ b/lekin/solver/construction_heuristics/atcs.py
@@ -0,0 +1,38 @@
+"""Apparent Tardiness Cost"""
+
+import logging
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class ATCScheduler(object):
+ def __init__(self, jobs, routes):
+ self.jobs = jobs
+ self.routes = routes
+
+ def calculate_tardiness_cost(self, operation):
+ # Calculate the tardiness cost for an operation based on its finish time and due date
+ if operation.end_time > operation.due_date:
+ return operation.end_time - operation.due_date
+ else:
+ return 0
+
+ def schedule_job(self, job):
+ # Schedule the operations of a job using ATC method
+ for operation in job.route.operations:
+ operation.start_time = max(operation.available_time, operation.earliest_start_time)
+ operation.end_time = operation.start_time + operation.processing_time
+
+ # Sort the operations by their tardiness cost in descending order
+ sorted_operations = sorted(job.route.operations, key=self.calculate_tardiness_cost, reverse=True)
+
+ # Reschedule the operations based on their tardiness cost
+ current_time = 0
+ for operation in sorted_operations:
+ operation.start_time = max(current_time, operation.earliest_start_time)
+ operation.end_time = operation.start_time + operation.processing_time
+ current_time = operation.end_time
+
+ def run(self):
+ for job in self.jobs:
+ self.schedule_job(job)
diff --git a/lekin/solver/construction_heuristics/base.py b/lekin/solver/construction_heuristics/base.py
new file mode 100644
index 0000000..9dca977
--- /dev/null
+++ b/lekin/solver/construction_heuristics/base.py
@@ -0,0 +1,19 @@
+import logging
+
+
+class BaseScheduler(object):
+ def __init__(self, job_collector, resource_collector, **kwargs):
+ self.job_collector = job_collector
+ self.resource_collector = resource_collector
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def run(self):
+ raise NotImplementedError
+
+ def scheduling_job(self, job, **kwargs):
+ raise NotImplementedError
+
+ def find_best_resource_and_timeslot_for_operation(self, operation, **kwargs):
+ raise NotImplementedError
diff --git a/lekin/solver/construction_heuristics/cr.py b/lekin/solver/construction_heuristics/cr.py
new file mode 100644
index 0000000..46a735c
--- /dev/null
+++ b/lekin/solver/construction_heuristics/cr.py
@@ -0,0 +1,30 @@
+"""Critical ratio rule"""
+
+import logging
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class CRScheduler(object):
+ def __init__(self, jobs, routes):
+ self.jobs = jobs
+ self.routes = routes
+
+ def calculate_critical_ratio(self, operation):
+ time_remaining = operation.job.due_date - operation.start_time
+ return time_remaining / operation.processing_time
+
+ def schedule_job(self, job):
+ # Schedule the operations of a job using CR method
+ current_time = 0
+ for operation in job.route.operations:
+ operation.start_time = max(current_time, operation.available_time)
+ operation.end_time = operation.start_time + operation.processing_time
+ current_time = operation.end_time
+
+ # Sort the operations based on critical ratio
+ job.route.operations.sort(key=self.calculate_critical_ratio, reverse=True)
+
+ def run(self):
+ for job in self.jobs:
+ self.schedule_job(job)
diff --git a/lekin/solver/construction_heuristics/edd.py b/lekin/solver/construction_heuristics/edd.py
new file mode 100644
index 0000000..07e1cfe
--- /dev/null
+++ b/lekin/solver/construction_heuristics/edd.py
@@ -0,0 +1,30 @@
+"""Earliest Due Date"""
+
+import logging
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class EDDScheduler(object):
+ def __init__(self, jobs, routes):
+ self.jobs = jobs
+ self.routes = routes
+
+ def schedule_job(self, job):
+ # Schedule the operations of a job using EDD method
+ current_time = 0
+ for operation in job.route.operations:
+ operation.start_time = max(current_time, operation.available_time)
+ operation.end_time = operation.start_time + operation.processing_time
+ current_time = operation.end_time
+
+ def run(self):
+ for job in self.jobs:
+ self.schedule_job(job)
+
+
+class MS(object):
+ """Variation of EDD"""
+
+ def __init__(self):
+ pass
diff --git a/lekin/solver/construction_heuristics/epst.py b/lekin/solver/construction_heuristics/epst.py
new file mode 100644
index 0000000..926a109
--- /dev/null
+++ b/lekin/solver/construction_heuristics/epst.py
@@ -0,0 +1,109 @@
+"""Earliest Possible Start Time
+Forward scheduler
+正排"""
+
+import logging
+import math
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class EPSTScheduler(BaseScheduler):
+ def __init__(self, job_collector, resource_collector, route_collector=None, **kwargs):
+ super().__init__(job_collector, resource_collector, **kwargs)
+ self.job_collector = job_collector
+ self.resource_collector = resource_collector
+ self.route_collector = route_collector
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def run(self):
+ for i, job in enumerate(self.job_collector.job_list):
+ self.scheduling_job(job, self.resource_collector, self.route_collector)
+ logging.info("First Scheduling Done")
+
+ for i, job in enumerate(self.job_collector.job_list):
+ self.rescheduling_job_to_resolve_conflict(job)
+ logging.info("ReScheduling Done")
+ return
+
+ def scheduling_job(self, job, resource_collector, route_collector):
+ logging.info(f"\nAssign Job {job.job_id}")
+
+ if route_collector is not None:
+ route_id = job.assigned_route_id
+ route = None
+ for r in route_collector:
+ if r.route_id == route_id:
+ route = r
+ break
+ if not route:
+ print(f"Route with ID '{job.assigned_route_id}' not found for Job ID '{job.job_id}'. Skipping job.")
+
+ job.operations = route.operations_sequence
+
+ op_earliest_start = 0
+ for operation in job.operations:
+ logging.info(f"\tAssign Operation {operation.operation_id} of Job {job.job_id}")
+ chosen_resource, chosen_timeslot_hour = self.find_best_resource_and_timeslot_for_operation(
+ operation, op_earliest_start
+ )
+
+ if chosen_resource and chosen_timeslot_hour:
+ logging.info(
+ f"\tOperation {operation.operation_id} assigned in: resource"
+ f" {chosen_resource.resource_id}, {min(chosen_timeslot_hour)} -"
+ f" {max(chosen_timeslot_hour)}"
+ )
+
+ # assign
+ operation.assigned_resource = chosen_resource
+ operation.assigned_hours = chosen_timeslot_hour
+ chosen_resource.assigned_operations.append(operation)
+ chosen_resource.assigned_hours += chosen_timeslot_hour
+
+ op_earliest_start = chosen_timeslot_hour[-1] + 1
+ return
+
+ def find_best_resource_and_timeslot_for_operation(self, operation, op_earliest_start, **kwargs):
+ available_resource = operation.available_resource
+
+ earliest_index = 0
+ resource_earliest_time = float("inf")
+ for i, resource in enumerate(available_resource):
+ resource_time = resource.get_earliest_available_time(duration=operation.processing_time)
+
+ if resource_time < resource_earliest_time:
+ earliest_index = i
+ resource_earliest_time = resource_time
+
+ chosen_resource = available_resource[earliest_index]
+ earliest_time = int(max(op_earliest_start, resource_earliest_time))
+ chosen_hours = list(range(earliest_time, earliest_time + math.ceil(operation.processing_time)))
+ return chosen_resource, chosen_hours
+
+ def rescheduling_job_to_resolve_conflict(self, job):
+ op_earliest_start = 0
+ for operation in job.operations:
+ logging.info(f"Rescheduling {job.job_id}/ {operation.operation_id}")
+ assigned_resource = operation.assigned_resource
+ if operation.assigned_hours[0] < op_earliest_start:
+ delta = op_earliest_start - operation.assigned_hours[0]
+ operation.assigned_hours = [i + delta for i in operation.assigned_hours]
+
+ pivot_assigned_hours = operation.assigned_hours
+ op_earliest_start = pivot_assigned_hours[-1] + 1
+
+ ops_in_same_resource = assigned_resource.assigned_operations
+ ops_in_same_resource.sort(key=lambda x: x.assigned_hours[0], reverse=False)
+ logging.info([i.parent_job_id for i in ops_in_same_resource])
+ for op in ops_in_same_resource:
+ if op != operation:
+ op_start = op.assigned_hours[0]
+ if set(pivot_assigned_hours).intersection(set(op.assigned_hours)):
+ logging.info(
+ f"\tRescheduling {job.job_id}/ {op.operation_id} in {assigned_resource.resource_id}"
+ )
+ op.assigned_hours = [i + pivot_assigned_hours[-1] - op_start + 1 for i in op.assigned_hours]
+ return
diff --git a/lekin/solver/construction_heuristics/fifo.py b/lekin/solver/construction_heuristics/fifo.py
new file mode 100644
index 0000000..232f840
--- /dev/null
+++ b/lekin/solver/construction_heuristics/fifo.py
@@ -0,0 +1,31 @@
+"""First In First Out"""
+
+import logging
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class FCFSScheduler:
+ """
+ - 初始化，记录各个机器前的任务等待序列。模拟时间进度
+ """
+
+ def __init__(self, jobs, routes):
+ self.jobs = jobs
+ self.routes = routes
+
+ def init(self):
+ """ """
+ pass
+
+ def schedule_job(self, job):
+ # Schedule the operations of a job in FCFS order
+ current_time = 0
+ for operation in job.route.operations:
+ operation.start_time = max(current_time, operation.available_time)
+ operation.end_time = operation.start_time + operation.processing_time
+ current_time = operation.end_time
+
+ def run(self):
+ for job in self.jobs:
+ self.schedule_job(job)
diff --git a/lekin/solver/construction_heuristics/lpst.py b/lekin/solver/construction_heuristics/lpst.py
new file mode 100644
index 0000000..c43dd97
--- /dev/null
+++ b/lekin/solver/construction_heuristics/lpst.py
@@ -0,0 +1,146 @@
+"""Latest Possible Start Time
+Backward scheduler
+倒排"""
+
+import logging
+import math
+
+from lekin.lekin_struct.job import Job, JobCollector
+from lekin.lekin_struct.operation import Operation
+from lekin.lekin_struct.resource import ResourceCollector
+from lekin.lekin_struct.route import RouteCollector
+from lekin.lekin_struct.timeslot import TimeSlot
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class LPSTScheduler(object):
+ def __init__(
+ self,
+ job_collector: JobCollector,
+ resource_collector: ResourceCollector,
+ route_collector: RouteCollector = None,
+ **kwargs,
+ ) -> None:
+ self.job_collector = job_collector
+ self.resource_collector = resource_collector
+ self.route_collector = route_collector
+
+ for key, value in kwargs.items():
+ setattr(self, key, value)
+
+ def run(self) -> None:
+ for i, job in enumerate(self.job_collector.job_list):
+ self.scheduling_job(job, self.resource_collector, self.route_collector)
+ logging.info("First Scheduling Done")
+ return
+
+ def scheduling_job(self, job: Job, resource_collector, route_collector: RouteCollector) -> None:
+ logging.info(f"\nAssign Job {job.job_id}")
+
+ if route_collector is not None:
+ route_id = job.assigned_route_id
+ route = None
+ for r in route_collector:
+ if r.route_id == route_id:
+ route = r
+ break
+ if not route:
+ print(f"Route with ID '{job.assigned_route_id}' not found for Job ID '{job.job_id}'. Skipping job.")
+
+ job.operations = route.operations_sequence
+
+ op_earliest_start = 0 # forward constraint
+ op_latest_end = 150 # backward constraint
+ for operation in job.operations[::-1]: # inverse
+ logging.info(f"\tAssign Operation {operation.operation_id} of Job {job.job_id}")
+ chosen_resource, chosen_timeslot_hour = self.find_best_resource_and_timeslot_for_operation(
+ operation, op_latest_end, op_earliest_start
+ )
+
+ if chosen_resource and chosen_timeslot_hour:
+ logging.info(
+ f"\tOperation {operation.operation_id} assigned in: resource"
+ f" {chosen_resource.resource_id}, {min(chosen_timeslot_hour)} -"
+ f" {max(chosen_timeslot_hour)}"
+ )
+
+ # assign
+ operation.assigned_resource = chosen_resource
+ operation.assigned_hours = chosen_timeslot_hour
+ chosen_resource.assigned_operations.append(operation)
+ chosen_resource.assigned_hours += chosen_timeslot_hour
+
+ # op_earliest_start = chosen_timeslot_hour[-1] + 1
+ op_latest_end = chosen_timeslot_hour[0] - 1
+ return
+
+ def find_best_resource_and_timeslot_for_operation(
+ self, operation: Operation, op_latest_end=None, op_earliest_start=None, **kwargs
+ ):
+ available_resource = operation.available_resource
+
+ latest_index = float("inf")
+ resource_latest_time = 0
+ for i, resource in enumerate(available_resource):
+ resource_time = resource.get_latest_available_time(duration=operation.processing_time, end=op_latest_end)
+
+ if resource_time > resource_latest_time:
+ latest_index = i
+ resource_latest_time = resource_time
+
+ chosen_resource = available_resource[latest_index]
+ latest_time = int(min(op_latest_end, resource_latest_time))
+ chosen_hours = list(range(latest_time - math.ceil(operation.processing_time), latest_time + 0))
+ return chosen_resource, chosen_hours
+
+ def assign_operation(self, operation: Operation, start_time, end_time, resources):
+ timeslot = TimeSlot(start_time, end_time)
+ self.timeslots.append(timeslot)
+ for resource in resources:
+ # Add timeslot to resource's schedule
+ resource.schedule.append(timeslot)
+ # Link operation to scheduled timeslot
+ operation.scheduled_timeslot = timeslot
+
+ def select_resources(self, job: Job, operation: Operation):
+ available_slots = self.find_available_timeslots(job, operation)
+
+ selected_resources = []
+ for slot in available_slots:
+ resources = slot.available_resources()
+ resource = self.optimize_resource_selection(resources, operation)
+ selected_resources.append((slot, resource))
+ return selected_resources
+
+ def find_available_timeslots(self, job, operation):
+ # Search timeslots and filter based on:
+ # - operation duration
+ # - predecessor timeslots
+ # - resource requirements
+
+ slots = []
+ # for ts in job.schedule.timeslots:
+ # if ts.end - ts.start >= operation.duration:
+ # if all(pred in job.predecessors(ts)):
+ # if ts.meets_resource_needs(operation):
+ # slots.append(ts)
+ return slots
+
+ def optimize_resource_selection(self, resources, operation):
+ # Score and prioritize resources based on:
+ # - Capacity
+ # - Changeover time
+ # - Utilization
+
+ scored = []
+ for resource in resources:
+ score = 0
+ if resource.capacity >= operation.required_capacity:
+ score += 1
+ if resource.type in operation.preferred_resources:
+ score += 1
+ # Prioritize resources with less adjacent timeslots
+ score -= len(resource.adjacent_timeslots(operation))
+ scored.append((score, resource))
+ best = max(scored, key=lambda x: x[0])
+ return best[1]
diff --git a/lekin/solver/construction_heuristics/lsf.py b/lekin/solver/construction_heuristics/lsf.py
new file mode 100644
index 0000000..ce25ed0
--- /dev/null
+++ b/lekin/solver/construction_heuristics/lsf.py
@@ -0,0 +1,46 @@
+"""L"""
+
+import logging
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class LSTScheduler(object):
+ def __init__(self, jobs, routes):
+ self.jobs = jobs
+ self.routes = routes
+
+ def calculate_slack_time(self, operation, current_time):
+ # Calculate the slack time for an operation based on its due date and current time
+ return max(0, operation.due_date - current_time)
+
+ def select_next_operation(self, available_operations, current_time):
+ # Select the operation with the longest slack time from the available operations
+ selected_operation = None
+ max_slack_time = float("-inf")
+
+ for operation in available_operations:
+ slack_time = self.calculate_slack_time(operation, current_time)
+ if slack_time > max_slack_time:
+ max_slack_time = slack_time
+ selected_operation = operation
+
+ return selected_operation
+
+ def schedule_job(self, job, start_time):
+ # Schedule the operations of a job based on LST
+ current_time = start_time
+
+ for operation in job.route.operations:
+ slack_time = self.calculate_slack_time(operation, current_time)
+ print(slack_time)
+ operation.start_time = current_time
+ operation.end_time = current_time + operation.processing_time
+ current_time += operation.processing_time
+
+ job.completion_time = current_time
+
+ def run(self):
+ for job in self.jobs:
+ self.schedule_job(job, 0)
diff --git a/lekin/solver/construction_heuristics/mix.py b/lekin/solver/construction_heuristics/mix.py
new file mode 100644
index 0000000..a74a1e7
--- /dev/null
+++ b/lekin/solver/construction_heuristics/mix.py
@@ -0,0 +1,72 @@
+import heapq
+
+
+class JobScheduler:
+ def __init__(self, available_slots, jobs, routes, operations, resources):
+ self.available_slots = available_slots
+ heapq.heapify(self.available_slots) # Convert the list into a min heap
+ self.jobs = jobs
+ self.routes = routes
+ self.operations = operations
+ self.resources = resources
+
+ def backward_schedule(self):
+ # Implement your initial backward scheduling pass here
+ pass
+
+ def assign_resource(self, operation, available_resources):
+ # Implement resource assignment logic based on availability and scoring
+ pass
+
+ def analyze_schedule_density(self):
+ # Implement schedule density analysis
+ pass
+
+ def identify_bottleneck_resources(self):
+ # Identify bottleneck resources limiting density
+ pass
+
+ def push_operations_closer(self, bottleneck_resources):
+ # Push operations closer on bottleneck resources
+ pass
+
+ def rescore_operations(self):
+ # Rescore operations based on priority and slack time
+ pass
+
+ def reassign_operations(self):
+ # Reassign operations to reduce gaps
+ pass
+
+ def reevaluate_routes(self, critical_jobs):
+ # Re-evaluate routes for critical jobs
+ pass
+
+ def reschedule_operations(self, critical_jobs):
+ # Reschedule operations on preferred resources for critical jobs
+ pass
+
+ def push_dense(self):
+ # Iteratively push operations closer system-wide
+ # while True:
+ # self.backward_schedule()
+ # density = self.analyze_schedule_density()
+ # if density is not improved:
+ # break
+ pass
+
+ def final_tweaking(self):
+ # Fine-tune schedules of critical jobs and leverage flexibilities
+ pass
+
+ def optimize_schedule(self):
+ self.push_dense()
+ critical_jobs = self.identify_critical_jobs()
+ self.reevaluate_routes(critical_jobs)
+ self.reschedule_operations(critical_jobs)
+ self.final_tweaking()
+ return self.schedule
+
+ def identify_critical_jobs(self):
+ # Identify critical jobs on the schedule
+ pass
diff --git a/lekin/solver/construction_heuristics/spt.py b/lekin/solver/construction_heuristics/spt.py
new file mode 100644
index 0000000..bd47e82
--- /dev/null
+++ b/lekin/solver/construction_heuristics/spt.py
@@ -0,0 +1,102 @@
+"""Shortest Processing Time
+"""
+
+from collections import OrderedDict
+import logging
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+
+from lekin.solver.construction_heuristics.base import BaseScheduler
+
+
+class SPTScheduler(object):
+ def __init__(self):
+ self.time = {} # global时间队列
+ self.waiting_operations = {} # 记录每个机器的任务等待队列
+ self.jobs_list_to_export = []
+
+ def setup(self, job_list: List, machine_list: List):
+ for machine in machine_list:
+ # init for machine start time
+ self.current_time_on_machines[machine.name] = 0
+
+ # init for waiting list of machines
+ self.waiting_operations[machine.name] = 0
+ for job in job_list:
+ if job.operation_id == 1 and machine.name in job.machine:
+ if len(job.machine) == 1:
+ self.waiting_operations[machine.name].append(job)
+
+ self.waiting_operations[machine.name].sort(key=lambda j: j.duration)
+ return
+
+ def solve(self, job_list: List, machine_list: List):
+ self.setup(job_list, machine_list)
+
+ self.time[0] = self.waiting_operations
+
+ for key_mach, operations in self.waiting_operations.items():
+ # for each waiting task in front of machine, set time to 0
+ if len(operations):
+ operations[0].start_time = 0
+ operations[0].completed = True
+ operations[0].assigned_machine = key_mach
+
+ self.jobs_list_to_export.append(operations[0])
+ self.current_time_on_machines[key_mach] = operations[0].get_end_time()
+ self.time[self.current_time_on_machines[key_mach]] = {}
+
+ while len(self.jobs_list_to_export) != len(job_list):
+ for t, operations in self.time.items():
+ operations = self.get_waiting_operations(
+ job_list, float(t), machine_list, self.current_time_on_machines
+ )
+
+ for key_mach, tasks in operations.items():
+ if len(tasks):
+ if float(t) < self.current_time_on_machines[key_mach]:
+ continue
+
+ tasks[0].start_time = float(t)
+ tasks[0].completed = True
+ tasks[0].assigned_machine = key_mach
+
+ self.jobs_list_to_export.append(tasks[0])
+ self.current_time_on_machines[key_mach] = tasks[0].get_end_time()
+ self.time[self.current_time_on_machines[key_mach]] = {}
+
+ del self.time[t]
+ break
+ self.time = OrderedDict(self.time)
+ return self.jobs_list_to_export
+
+ def get_waiting_operations(self, job_list, time, machine_list, current_time_on_machines):
+ incoming_operations = {}
+
+ for mach in machine_list:
+ assigned_jobs_for_machine = []
+ for job in job_list:
+ if job.completed is False and mach.name in job.machine:
+ if len(job.machine) == 1:
+ assigned_jobs_for_machine.append(job)
+
+ incoming_operations[mach.name] = []
+ for j in assigned_jobs_for_machine:
+ if j.id_operation == 1:
+ incoming_operations[mach.name].append(j)
+ else:
+ previous_task = [
+ job
+ for job in job_list
+ if job.route_id == j.route_id
+ and job.id_operation == (j.id_operation - 1)
+ and job.end_time <= time
+ ]
+ if len(previous_task):
+ if previous_task[0].completed:
+ incoming_operations[mach.name].append(j)
+
+ incoming_operations[mach.name].sort(key=lambda j: j.duration)
+ return incoming_operations
+
+ def run(self):
+ return
diff --git a/lekin/solver/meta_heuristics/__init__.py b/lekin/solver/meta_heuristics/__init__.py
new file mode 100644
index 0000000..e8ba164
--- /dev/null
+++ b/lekin/solver/meta_heuristics/__init__.py
@@ -0,0 +1,6 @@
+"""Heuristics"""
+
+
+class Heuristics(object):
+ def __init__(self, name):
+ pass
diff --git a/lekin/solver/meta_heuristics/branch_and_bound.py b/lekin/solver/meta_heuristics/branch_and_bound.py
new file mode 100644
index 0000000..0734e06
--- /dev/null
+++ b/lekin/solver/meta_heuristics/branch_and_bound.py
@@ -0,0 +1,57 @@
+from datetime import datetime, timedelta
+from itertools import permutations
+
+from lekin.lekin_struct import TimeSlot
+
+
+class BranchAndBoundScheduler:
+ def __init__(self, job_list, resource_list):
+ self.job_list = job_list
+ self.resource_list = resource_list
+ self.best_schedule = None
+ self.best_cost = float("inf")
+
+ def find_available_time_slots(self, operation, resource, current_time):
+ # Implement the logic to find available time slots for a given operation and resource
+ available_time_slots = []
+ for slot in resource.available_time_slots:
+ if slot.start_time >= current_time + operation.processing_time:
+ available_time_slots.append(slot)
+ return available_time_slots
+
+ def assign_operation(self, job, operation, resource, start_time):
+ # Implement the logic to assign an operation to a resource at a specific start time
+ end_time = start_time + operation.processing_time
+ resource.available_time_slots.append(TimeSlot(end_time, float("inf")))
+ return end_time
+
+ def calculate_cost(self, schedule):
+ # Implement the logic to calculate the cost of the current schedule
+ # For example, you can calculate makespan or any other relevant metric
+ makespan = max(slot.end_time for slot in schedule)
+ return makespan
+
+ def branch_and_bound(self, current_job_idx, current_time, schedule):
+ # Implement the Branch and Bound algorithm for scheduling
+ if current_job_idx == len(self.job_list):
+ cost = self.calculate_cost(schedule)
+ if cost < self.best_cost:
+ self.best_cost = cost
+ self.best_schedule = schedule.copy()
+ return
+
+ job = self.job_list[current_job_idx]
+ route = self.resource_list[job.assigned_route_id]
+
+ for resource_id in route.operations[0].resource_ids:
+ resource = self.resource_list[resource_id]
+ time_slots = self.find_available_time_slots(route.operations[0], resource, current_time)
+ for slot in time_slots:
+ new_schedule = schedule + [slot]
+ new_time = self.assign_operation(job, route.operations[0], resource, slot.start_time)
+ self.branch_and_bound(current_job_idx + 1, new_time, new_schedule)
+
+ def get_schedule(self):
+ # Implement the main function to get the final schedule using Branch and Bound
+ self.branch_and_bound(0, datetime(2023, 1, 1), [])
+ return self.best_schedule
diff --git a/lekin/solver/meta_heuristics/critical_path.py b/lekin/solver/meta_heuristics/critical_path.py
new file mode 100644
index 0000000..4f88e1a
--- /dev/null
+++ b/lekin/solver/meta_heuristics/critical_path.py
@@ -0,0 +1,70 @@
+"""Critical path"""
+
+import copy
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+
+class CriticalPathScheduler:
+ def __init__(self, job_collector):
+ self.job_collector = job_collector
+
+ def schedule(self):
+ # Generate the forward and backward pass times
+ forward_pass_times = self.forward_pass()
+ backward_pass_times = self.backward_pass()
+
+ # Find the critical path
+ critical_path = self.find_critical_path(forward_pass_times, backward_pass_times)
+
+ # Assign start times for each operation in the critical path
+ critical_path_schedule = {}
+ current_time = 0
+ for job_id, operation_id in critical_path:
+ operation = self.job_collector.get_operation_by_id(job_id, operation_id)
+ critical_path_schedule[operation] = current_time
+ current_time += operation.processing_time
+
+ return critical_path_schedule
+
+ def forward_pass(self):
+ forward_pass_times: Dict[str, Dict[str, float]] = {}
+ for job in self.job_collector.jobs:
+ forward_pass_times[job.id] = {}
+ for operation in job.route.operations:
+ if operation.id == 0:
+ forward_pass_times[job.id][operation.id] = 0
+ else:
+ predecessors = operation.get_predecessors()
+ max_predecessor_time = max(
+ [forward_pass_times[job.id][pred.id] + pred.processing_time for pred in predecessors]
+ )
+ forward_pass_times[job.id][operation.id] = max_predecessor_time
+
+ return forward_pass_times
+
+ def backward_pass(self):
+ backward_pass_times: Dict[str, Dict[str, float]] = {}
+ for job in self.job_collector.jobs:
+ backward_pass_times[job.id] = {}
+ for operation in reversed(job.route.operations):
+ if operation.id == len(job.route.operations) - 1:
+ backward_pass_times[job.id][operation.id] = operation.processing_time
+ else:
+ successors = operation.get_successors()
+ min_successor_time = min(
+ [backward_pass_times[job.id][succ.id] + succ.processing_time for succ in successors]
+ )
+ backward_pass_times[job.id][operation.id] = min_successor_time
+
+ return backward_pass_times
+
+ def find_critical_path(self, forward_pass_times, backward_pass_times):
+ critical_path = []
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ start_time = forward_pass_times[job.id][operation.id]
+ end_time = backward_pass_times[job.id][operation.id]
+ if start_time + operation.processing_time == end_time:
+ critical_path.append((job.id, operation.id))
+
+ return critical_path
diff --git a/lekin/solver/meta_heuristics/genetic.py b/lekin/solver/meta_heuristics/genetic.py
new file mode 100644
index 0000000..0dba9ba
--- /dev/null
+++ b/lekin/solver/meta_heuristics/genetic.py
@@ -0,0 +1,98 @@
+"""Genetic scheduler"""
+
+import copy
+import random
+
+from lekin.lekin_struct import JobCollector, ResourceCollector, RouteCollector
+
+
+class GeneticScheduler:
+ def __init__(
+ self,
+ job_collector: JobCollector,
+ resource_collector: ResourceCollector,
+ route_collector: RouteCollector = None,
+ initial_schedule=None,
+ population_size=50,
+ generations=1000,
+ crossover_rate=0.8,
+ mutation_rate=0.2,
+ **kwargs,
+ ):
+ self.job_collector = job_collector
+ self.initial_schedule = initial_schedule
+ self.population_size = population_size
+ self.generations = generations
+ self.crossover_rate = crossover_rate
+ self.mutation_rate = mutation_rate
+
+ def run(self):
+ population = self.initialize_population()
+
+ for generation in range(self.generations):
+ selected_individuals = self.selection(population)
+ new_population = []
+
+ while len(new_population) < self.population_size:
+ parent1 = random.choice(selected_individuals)
+ parent2 = random.choice(selected_individuals)
+
+ if random.random() < self.crossover_rate:
+ offspring1, offspring2 = self.crossover(parent1, parent2)
+ else:
+ offspring1, offspring2 = parent1, parent2
+
+ if random.random() < self.mutation_rate:
+ offspring1 = self.mutation(offspring1)
+ if random.random() < self.mutation_rate:
+ offspring2 = self.mutation(offspring2)
+
+ new_population.append(offspring1)
+ new_population.append(offspring2)
+
+ population = new_population
+
+ # Find the best solution in the final population
+ best_solution = min(population, key=lambda chromosome: self.fitness(chromosome)[0])
+
+ # Return the best schedule
+ return self.job_collector.create_schedule_from_operations(best_solution)
+
+ def initialize_population(self):
+ population = []
+ for _ in range(self.population_size):
+ # Shuffle the operations for each job to create a random chromosome
+ chromosome = copy.deepcopy(self.job_collector.get_operations())
+ for job_operations in chromosome.values():
+ random.shuffle(job_operations)
+ population.append(chromosome)
+ return population
+
+ def fitness(self, chromosome):
+ # Calculate the fitness of a chromosome based on the scheduling criteria (e.g., makespan, tardiness)
+ # The lower the fitness value, the better the solution
+ # Return a tuple with the fitness value and the schedule
+ schedule = self.job_collector.create_schedule_from_operations(chromosome)
+ fitness_value = 0
+ return fitness_value, schedule
+
+ def selection(self, population):
+ # Select the best individuals based on their fitness values
+ # You can use tournament selection, rank-based selection, or other methods
+ # Return the selected individuals
+ selected_individuals = 0
+ return selected_individuals
+
+ def crossover(self, parent1, parent2):
+ # Perform crossover (recombination) between two parents to create two offspring
+ # You can use one-point crossover, two-point crossover, or other methods
+ # Return the two offspring
+ offspring1, offspring2 = 0, 0
+ return offspring1, offspring2
+
+ def mutation(self, chromosome):
+ # Introduce random changes in the chromosome to add diversity
+ # You can swap two operations for a randomly selected job
+ # Return the mutated chromosome
+ mutated_chromosome = 0
+ return mutated_chromosome
diff --git a/lekin/solver/meta_heuristics/hill_climbing.py b/lekin/solver/meta_heuristics/hill_climbing.py
new file mode 100644
index 0000000..dac23ae
--- /dev/null
+++ b/lekin/solver/meta_heuristics/hill_climbing.py
@@ -0,0 +1,60 @@
+"""Hill climbing"""
+
+import random
+
+
+class HillClimbingScheduler:
+ def __init__(self, job_collector):
+ self.job_collector = job_collector
+
+ def schedule(self, max_iterations=1000):
+ current_solution = self.random_solution()
+ current_score = self.evaluate_solution(current_solution)
+
+ for _ in range(max_iterations):
+ neighbors = self.get_neighbors(current_solution)
+ if not neighbors:
+ break
+
+ next_solution = max(neighbors, key=lambda neighbor: self.evaluate_solution(neighbor))
+ next_score = self.evaluate_solution(next_solution)
+
+ if next_score <= current_score:
+ current_solution = next_solution
+ current_score = next_score
+ else:
+ break
+
+ return current_solution
+
+ def random_solution(self):
+ return {
+ operation: random.randint(0, operation.get_latest_start_time())
+ for job in self.job_collector.jobs
+ for operation in job.route.operations
+ }
+
+ def get_neighbors(self, solution):
+ neighbors = []
+ for operation, start_time in solution.items():
+ for t in range(start_time - 1, operation.get_latest_start_time() + 1):
+ neighbor = solution.copy()
+ neighbor[operation] = t
+ neighbors.append(neighbor)
+ return neighbors
+
+ def evaluate_solution(self, solution):
+ end_times = {}
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ if operation in solution:
+ start_time = solution[operation]
+ else:
+ start_time = operation.get_latest_start_time()
+
+ end_time = start_time + operation.processing_time
+ if operation.id not in end_times or end_time > end_times[operation.id]:
+ end_times[operation.id] = end_time
+
+ makespan = max(end_times.values())
+ return makespan
diff --git a/lekin/solver/meta_heuristics/nsga3.py b/lekin/solver/meta_heuristics/nsga3.py
new file mode 100644
index 0000000..e25a2ee
--- /dev/null
+++ b/lekin/solver/meta_heuristics/nsga3.py
@@ -0,0 +1,87 @@
+import random
+from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union
+
+
+class NSGA3Scheduler:
+ def __init__(self, jobs, routes, num_generations, population_size):
+ self.jobs = jobs
+ self.routes = routes
+ self.num_generations = num_generations
+ self.population_size = population_size
+ self.population = []
+ self.fronts = []
+
+ def initialize_population(self):
+ # Generate an initial random population
+ for _ in range(self.population_size):
+ solution = self.generate_random_solution()
+ self.population.append(solution)
+
+ def generate_random_solution(self):
+ # Generate a random solution representing start times for operations
+ solution: Dict = {}
+ for job in self.jobs:
+ solution[job] = {}
+ for operation in job.route.operations:
+ solution[job][operation] = random.randint(0, 100) # Random start time
+ return solution
+
+ def evaluate_objectives(self, solution):
+ # Evaluate the objectives for a given solution
+ makespan = self.calculate_makespan(solution)
+ total_tardiness = self.calculate_total_tardiness(solution)
+ resource_utilization = self.calculate_resource_utilization(solution)
+ return makespan, total_tardiness, resource_utilization
+
+ def calculate_makespan(self, solution):
+ # Calculate the makespan for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def calculate_total_tardiness(self, solution):
+ # Calculate the total tardiness for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def calculate_resource_utilization(self, solution):
+ # Calculate the resource utilization for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def run(self):
+ self.initialize_population()
+ for generation in range(self.num_generations):
+ self.fast_nondominated_sort()
+ self.crowding_distance()
+ self.selection()
+ self.crossover()
+ self.mutation()
+
+ def fast_nondominated_sort(self):
+ # Implement NSGA-III's fast non-dominated sorting
+ # Categorize solutions into different fronts based on their dominance relationships
+ pass
+
+ def crowding_distance(self):
+ # Implement NSGA-III's crowding distance calculation
+ # Calculate the crowding distance for each solution in each front
+ pass
+
+ def selection(self):
+ # Implement NSGA-III's selection mechanism
+ # Select the best solutions based on their non-dominated ranks and crowding distances
+ pass
+
+ def crossover(self):
+ # Implement NSGA-III's crossover operator
+ # Perform crossover to create offspring solutions
+ pass
+
+ def mutation(self):
+ # Implement NSGA-III's mutation operator
+ # Perform mutation to introduce diversity in the population
+ pass
+
+ def get_pareto_front(self):
+ # Get the Pareto front solutions after the algorithm has run
+ return self.fronts[0]
diff --git a/lekin/solver/meta_heuristics/pso.py b/lekin/solver/meta_heuristics/pso.py
new file mode 100644
index 0000000..e0ce0ce
--- /dev/null
+++ b/lekin/solver/meta_heuristics/pso.py
@@ -0,0 +1 @@
+"""particle swarm optimization"""
diff --git a/lekin/solver/meta_heuristics/shifting_bottle_neck.py b/lekin/solver/meta_heuristics/shifting_bottle_neck.py
new file mode 100644
index 0000000..8dd031d
--- /dev/null
+++ b/lekin/solver/meta_heuristics/shifting_bottle_neck.py
@@ -0,0 +1,63 @@
+"""Shifting bottle neck meta_heuristics"""
+
+import copy
+
+
+class ShiftingBottleneckScheduler:
+ def __init__(self, job_collector):
+ self.job_collector = job_collector
+
+ def schedule(self):
+ best_solution = self.generate_initial_solution()
+ best_cost = self.calculate_cost(best_solution)
+
+ for _ in range(1000): # Number of iterations
+ current_solution = copy.deepcopy(best_solution)
+ bottleneck_job, bottleneck_op = self.find_bottleneck_operation(current_solution)
+
+ # Move bottleneck operation to different time slots
+ for time_slot in range(self.job_collector.max_time):
+ current_solution[bottleneck_job.id][bottleneck_op.id] = time_slot
+ current_cost = self.calculate_cost(current_solution)
+
+ if current_cost < best_cost:
+ best_solution = current_solution
+ best_cost = current_cost
+
+ return best_solution
+
+ def generate_initial_solution(self):
+ # Randomly assign operations to time slots
+ solution = {}
+ for job in self.job_collector.jobs:
+ solution[job.id] = {op.id: 0 for op in job.route.operations}
+ return solution
+
+ def find_bottleneck_operation(self, solution):
+ # Find the operation with the longest processing time in the schedule
+ max_processing_time = 0
+ bottleneck_job = None
+ bottleneck_op = None
+
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ processing_time = operation.processing_time
+ start_time = solution[job.id][operation.id]
+ end_time = start_time + processing_time
+
+ if end_time > max_processing_time:
+ max_processing_time = end_time
+ bottleneck_job = job
+ bottleneck_op = operation
+
+ return bottleneck_job, bottleneck_op
+
+ def calculate_cost(self, solution):
+ # Calculate the makespan of the schedule
+ max_end_time = 0
+ for job in self.job_collector.jobs:
+ end_time = max(
+ [solution[job.id][operation.id] + operation.processing_time for operation in job.route.operations]
+ )
+ max_end_time = max(max_end_time, end_time)
+ return max_end_time
diff --git a/lekin/solver/meta_heuristics/tabu_search.py b/lekin/solver/meta_heuristics/tabu_search.py
new file mode 100644
index 0000000..025d936
--- /dev/null
+++ b/lekin/solver/meta_heuristics/tabu_search.py
@@ -0,0 +1,74 @@
+"""
+Local search
+https://towardsdatascience.com/optimization-techniques-tabu-search-36f197ef8e25
+"""
+
+
+import math
+import random
+
+
+class TabuSearchScheduler:
+ def __init__(self, job_collector, max_iterations=1000, tabu_size=20):
+ self.job_collector = job_collector
+ self.max_iterations = max_iterations
+ self.tabu_size = tabu_size
+
+ def schedule(self):
+ best_solution = self.generate_initial_solution()
+ best_cost = self.calculate_cost(best_solution)
+
+ tabu_list = [best_solution]
+ current_solution = best_solution
+
+ for iteration in range(self.max_iterations):
+ neighbors = self.generate_neighbors(current_solution)
+ non_tabu_neighbors = [neighbor for neighbor in neighbors if neighbor not in tabu_list]
+
+ if not non_tabu_neighbors:
+ break
+
+ current_solution = random.choice(non_tabu_neighbors)
+ current_cost = self.calculate_cost(current_solution)
+
+ if current_cost < best_cost:
+ best_solution = current_solution
+ best_cost = current_cost
+
+ tabu_list.append(current_solution)
+ if len(tabu_list) > self.tabu_size:
+ tabu_list.pop(0)
+
+ return best_solution
+
+ def generate_initial_solution(self):
+ # Randomly assign operations to time slots
+ solution = {}
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ solution[(job.id, operation.id)] = random.randint(
+ 0, self.job_collector.max_time - operation.processing_time
+ )
+ return solution
+
+ def generate_neighbors(self, solution):
+ neighbors = []
+ for i in range(len(solution)):
+ neighbor = solution.copy()
+ job_id, operation_id = list(neighbor.keys())[i]
+ operation = self.job_collector.get_operation_by_id(job_id, operation_id)
+ neighbor[(job_id, operation_id)] = random.randint(
+ 0, self.job_collector.max_time - operation.processing_time
+ )
+ neighbors.append(neighbor)
+ return neighbors
+
+ def calculate_cost(self, solution):
+ # Calculate the makespan of the schedule
+ max_end_time = 0
+ for job in self.job_collector.jobs:
+ end_time = max(
+ [solution[(job.id, operation.id)] + operation.processing_time for operation in job.route.operations]
+ )
+ max_end_time = max(max_end_time, end_time)
+ return max_end_time
diff --git a/lekin/solver/meta_heuristics/variable_neighborhood_search.py b/lekin/solver/meta_heuristics/variable_neighborhood_search.py
new file mode 100644
index 0000000..57ae2d8
--- /dev/null
+++ b/lekin/solver/meta_heuristics/variable_neighborhood_search.py
@@ -0,0 +1,89 @@
+"""Variable neighborhood search"""
+
+import random
+
+
+class VNSScheduler:
+ def __init__(self, jobs, routes, max_iterations, neighborhood_size):
+ self.jobs = jobs
+ self.routes = routes
+ self.max_iterations = max_iterations
+ self.neighborhood_size = neighborhood_size
+
+ def initialize_solution(self):
+ # Generate an initial random solution representing start times for operations
+ solution = {}
+ for job in self.jobs:
+ solution[job] = {}
+ for operation in job.route.operations:
+ solution[job][operation] = random.randint(0, 100) # Random start time
+ return solution
+
+ def evaluate_objectives(self, solution):
+ # Evaluate the objectives for a given solution
+ makespan = self.calculate_makespan(solution)
+ total_tardiness = self.calculate_total_tardiness(solution)
+ resource_utilization = self.calculate_resource_utilization(solution)
+ return makespan, total_tardiness, resource_utilization
+
+ def calculate_makespan(self, solution):
+ # Calculate the makespan for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def calculate_total_tardiness(self, solution):
+ # Calculate the total tardiness for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def calculate_resource_utilization(self, solution):
+ # Calculate the resource utilization for a given solution
+ # Implementation specific to your job shop scheduling problem
+ pass
+
+ def generate_neighbor(self, current_solution):
+ # Generate a neighbor solution by perturbing the current solution
+ # You can use different perturbation techniques like swap, insert, etc.
+ # based on your specific problem requirements
+ neighbor_solution = current_solution.copy()
+ # Implement your perturbation here
+ return neighbor_solution
+
+ def accept_neighbor(self, current_solution, neighbor_solution, temperature):
+ # Decide whether to accept the neighbor solution based on acceptance criteria
+ # For VNS, you can use simulated annealing-like acceptance probability
+ # based on the difference in objective values and the current temperature
+ current_objectives = self.evaluate_objectives(current_solution)
+ neighbor_objectives = self.evaluate_objectives(neighbor_solution)
+ current_cost = self.calculate_cost(current_objectives)
+ neighbor_cost = self.calculate_cost(neighbor_objectives)
+
+ if neighbor_cost < current_cost:
+ return True
+ else:
+ acceptance_prob = min(1, pow(2.71, -(neighbor_cost - current_cost) / temperature))
+ return random.random() < acceptance_prob
+
+ def calculate_cost(self, objectives):
+ # Calculate the cost for a set of objectives
+ # You can define a weighted sum, weighted sum of ranks, or other measures
+ # based on your specific problem requirements and preferences
+ # For example, you can use a weighted sum of makespan and total tardiness
+ weight_makespan = 1
+ weight_tardiness = 1
+ return weight_makespan * objectives[0] + weight_tardiness * objectives[1]
+
+ def run(self):
+ current_solution = self.initialize_solution()
+ temperature = 100 # Initial temperature for simulated annealing
+ iteration = 0
+
+ while iteration < self.max_iterations:
+ for _ in range(self.neighborhood_size):
+ neighbor_solution = self.generate_neighbor(current_solution)
+ if self.accept_neighbor(current_solution, neighbor_solution, temperature):
+ current_solution = neighbor_solution
+ temperature *= 0.95 # Reduce temperature for simulated annealing
+ iteration += 1
+
+ return current_solution
diff --git a/lekin/solver/operation_research/__init__.py b/lekin/solver/operation_research/__init__.py
new file mode 100644
index 0000000..8b878dd
--- /dev/null
+++ b/lekin/solver/operation_research/__init__.py
@@ -0,0 +1 @@
+"""Operation research"""
diff --git a/lekin/solver/operation_research/ortool.py b/lekin/solver/operation_research/ortool.py
new file mode 100644
index 0000000..5d1c26a
--- /dev/null
+++ b/lekin/solver/operation_research/ortool.py
@@ -0,0 +1,69 @@
+from ortools.sat.python import cp_model
+
+
+class ORToolsScheduler:
+ def __init__(self, job_collector):
+ self.job_collector = job_collector
+ self.model = cp_model.CpModel()
+ self.vars = {}
+
+ def schedule(self):
+ self.create_variables()
+ self.add_constraints()
+ self.add_objective()
+ solver = cp_model.CpSolver()
+ status = solver.Solve(self.model)
+ if status == cp_model.OPTIMAL:
+ return self.get_schedule(solver)
+ else:
+ return None
+
+ def create_variables(self):
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ self.vars[operation.id] = self.model.NewIntVar(
+ 0, self.job_collector.max_time, f"Operation_{operation.id}_Start"
+ )
+
+ def add_constraints(self):
+ for job in self.job_collector.jobs:
+ for i, operation in enumerate(job.route.operations):
+ # Constraint: Each operation starts after the end of its parent operation
+ if i > 0:
+ parent_operation = job.route.operations[i - 1]
+ self.model.Add(
+ self.vars[operation.id] >= self.vars[parent_operation.id] + parent_operation.processing_time
+ )
+
+ # Constraint: Each operation must be finished before the job's demand date
+ self.model.Add(self.vars[operation.id] + operation.processing_time <= job.demand_date)
+
+ for resource in self.job_collector.resources:
+ for timeslot in resource.timeslots:
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ # Constraint: The operation must start within the resource's available timeslots
+ self.model.Add(self.vars[operation.id] >= timeslot.start_time).OnlyEnforceIf(timeslot.is_used)
+ self.model.Add(
+ self.vars[operation.id] <= timeslot.end_time - operation.processing_time
+ ).OnlyEnforceIf(timeslot.is_used)
+
+ def add_objective(self):
+ objective_var = self.model.NewIntVar(0, self.job_collector.max_time, "Makespan")
+ self.model.AddMaxEquality(
+ objective_var,
+ [
+ self.vars[operation.id] + operation.processing_time
+ for job in self.job_collector.jobs
+ for operation in job.route.operations
+ ],
+ )
+ self.model.Minimize(objective_var)
+
+ def get_schedule(self, solver):
+ schedule = {}
+ for job in self.job_collector.jobs:
+ for operation in job.route.operations:
+ start_time = solver.Value(self.vars[operation.id])
+ schedule[(job.id, operation.id)] = start_time
+ return schedule
diff --git a/lekin/solver/reinforcement_learning/__init__.py b/lekin/solver/reinforcement_learning/__init__.py
new file mode 100644
index 0000000..47e826e
--- /dev/null
+++ b/lekin/solver/reinforcement_learning/__init__.py
@@ -0,0 +1 @@
+"""Reinforcement learning"""
diff --git a/lekin/solver/reinforcement_learning/dqn.py b/lekin/solver/reinforcement_learning/dqn.py
new file mode 100644
index 0000000..751fc42
--- /dev/null
+++ b/lekin/solver/reinforcement_learning/dqn.py
@@ -0,0 +1,99 @@
+import random
+
+import numpy as np
+import tensorflow as tf
+
+
+class DeepQLearningScheduler:
+ def __init__(
+ self,
+ job_collector,
+ state_shape,
+ action_shape,
+ learning_rate=0.001,
+ gamma=0.99,
+ epsilon=1.0,
+ epsilon_decay=0.995,
+ epsilon_min=0.01,
+ ):
+ self.job_collector = job_collector
+ self.state_shape = state_shape
+ self.action_shape = action_shape
+ self.learning_rate = learning_rate
+ self.gamma = gamma
+ self.epsilon = epsilon
+ self.epsilon_decay = epsilon_decay
+ self.epsilon_min = epsilon_min
+
+ self.memory = []
+ self.q_network = self.build_q_network()
+ self.target_q_network = self.build_q_network()
+ self.update_target_network()
+
+ def build_q_network(self):
+ model = tf.keras.Sequential(
+ [
+ tf.keras.layers.Dense(64, activation="relu", input_shape=self.state_shape),
+ tf.keras.layers.Dense(64, activation="relu"),
+ tf.keras.layers.Dense(np.prod(self.action_shape), activation="linear"),
+ ]
+ )
+ model.compile(optimizer=tf.keras.optimizers.Adam(lr=self.learning_rate), loss="mse")
+ return model
+
+ def update_target_network(self):
+ self.target_q_network.set_weights(self.q_network.get_weights())
+
+ def get_action(self, state):
+ if np.random.rand() <= self.epsilon:
+ return np.random.randint(0, np.prod(self.action_shape))
+ return np.argmax(self.q_network.predict(np.array([state])))
+
+ def remember(self, state, action, reward, next_state, done):
+ self.memory.append((state, action, reward, next_state, done))
+
+ def replay(self, batch_size):
+ if len(self.memory) < batch_size:
+ return
+
+ batch = random.sample(self.memory, batch_size)
+
+ states = np.array([experience[0] for experience in batch])
+ actions = np.array([experience[1] for experience in batch])
+ rewards = np.array([experience[2] for experience in batch])
+ next_states = np.array([experience[3] for experience in batch])
+ dones = np.array([experience[4] for experience in batch])
+
+ targets = rewards + self.gamma * (1 - dones) * np.amax(self.target_q_network.predict(next_states), axis=1)
+ target_f = self.q_network.predict(states)
+ target_f[np.arange(batch_size), actions] = targets
+
+ self.q_network.fit(states, target_f, epochs=1, verbose=0)
+
+ if self.epsilon > self.epsilon_min:
+ self.epsilon *= self.epsilon_decay
+
+ def train(self, episodes, batch_size):
+ for episode in range(episodes):
+ state = self.job_collector.get_state()
+ done = False
+
+ while not done:
+ action = self.get_action(state)
+ next_state, reward, done = self.job_collector.step(action)
+ self.remember(state, action, reward, next_state, done)
+ state = next_state
+
+ if len(self.memory) > batch_size:
+ self.replay(batch_size)
+
+ if episode % 10 == 0:
+ self.update_target_network()
+
+ def get_schedule(self):
+ state = self.job_collector.get_state()
+ done = False
+ while not done:
+ action = np.argmax(self.q_network.predict(np.array([state])))
+ state, _, done = self.job_collector.step(action)
+ return self.job_collector.get_schedule()
diff --git a/lekin/solver/utils/__init__.py b/lekin/solver/utils/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/solver/utils/push_dense.py b/lekin/solver/utils/push_dense.py
new file mode 100644
index 0000000..425528e
--- /dev/null
+++ b/lekin/solver/utils/push_dense.py
@@ -0,0 +1,28 @@
+def push_dense(schedule):
+ changed = True
+
+ while changed:
+ changed = False
+
+ for resource in schedule.resources:
+ slots = sorted(resource.slots, key=lambda x: x.start_time)
+
+ for i in range(len(slots) - 1):
+ curr_slot = slots[i]
+ next_slot = slots[i + 1]
+
+ if curr_slot.end_time < next_slot.start_time:
+ # Gap exists between operations
+
+ gap = next_slot.start_time - curr_slot.end_time
+
+ if next_slot.operation.can_start_early(gap):
+ # Update slots
+ next_slot.start_time -= gap
+ next_slot.end_time -= gap
+
+ curr_slot.end_time = next_slot.start_time
+
+ changed = True
+
+ return schedule
diff --git a/lekin/utils/__init__.py b/lekin/utils/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/lekin/utils/group_op_ds.py b/lekin/utils/group_op_ds.py
new file mode 100644
index 0000000..0f27e13
--- /dev/null
+++ b/lekin/utils/group_op_ds.py
@@ -0,0 +1,67 @@
+"""
+新加入的时候可以快速找到该节点，因此之前用了dict[id, MaterialOP]
+
+移动的时候, 先标记一些candidate
+
+找到一个candidate, 往前找之前的插入位置
+
+重新整理
+
+"""
+
+
+class DictNode:
+ def __init__(self, key, value):
+ self.key = key
+ self.value = value
+ self.prev = None
+ self.next = None
+
+
+from collections import OrderedDict
+
+class IndexedList:
+ def __init__(self):
+ self.ordered_dict = OrderedDict()
+ self.order_list = []
+
+ def insert_at_index(self, index, key, value):
+ if index < 0 or index > len(self.order_list):
+ raise IndexError("Index out of bounds")
+
+ self.ordered_dict[key] = value
+ self.order_list.insert(index, key)
+
+ def insert_after(self, key, new_key, new_value):
+ if key is None:
+ # Insert at the beginning
+ self.ordered_dict[new_key] = new_value
+ elif key in self.ordered_dict:
+ # Insert after the specified key
+ items = list(self.ordered_dict.items())
+ index = next((i for i, (k, v) in enumerate(items) if k == key), -1)
+ if index != -1:
+ items.insert(index + 1, (new_key, new_value))
+ self.ordered_dict = OrderedDict(items)
+ else:
+ raise KeyError(f"Key '{key}' not found in the indexed list")
+ else:
+ raise KeyError(f"Key '{key}' not found in the indexed list")
+
+ def display(self):
+ for key, value in self.ordered_dict.items():
+ print(f"({key}: {value})", end=" ")
+ print()
+
+
+# Example Usage:
+indexed_list = IndexedList()
+indexed_list.insert_at_index(0, 'a', 1)
+indexed_list.insert_at_index(1, 'b', 2)
+indexed_list.insert_at_index(1, 'c', 3)
+indexed_list.display() # Output: (a: 1) (c: 3) (b: 2)
+
+indexed_list.insert_at_index(2, 'd', 4)
+indexed_list.display() # Output: (a: 1) (c: 3) (d: 4) (b: 2)
+
+
diff --git a/lekin/utils/push_dense.py b/lekin/utils/push_dense.py
new file mode 100644
index 0000000..a3de2b8
--- /dev/null
+++ b/lekin/utils/push_dense.py
@@ -0,0 +1,17 @@
+# push dense
+# for i, (id, resource) in enumerate(resource_collector.resources_dict.items()):
+# logging.info(
+# f'Start to push {i + 1}/{len(resource_collector.resources_dict)} resources'
+# )
+# assigned_ops = resource.assigned_operations
+# assigned_ops.sort()
+# for op in assigned_ops:
+# buffer_push = op.buffer
+# if buffer_push > resource.available_capacity:
+# buffer_push = resource.available_capacity
+
+# op.start_time -= buffer_push
+
+# # last chance for remaining jobs
+# for job in self.unassigned_jobs:
+# logging.warning(f'Abnornal! No scheduling for job {job.job_id}')
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 0000000..d0daceb
--- /dev/null
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+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.7"
+files = [
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+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.7,<3.11"
+content-hash = "c5b23e5b5be0d2103faf86cd3e0380fb6bfcd5e5b56e90dda009eb15e84fb619"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..cb6dae0
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,91 @@
+[tool.black]
+line-length = 120
+include = '\.pyi?$'
+exclude = '''
+(
+ /(
+ \.eggs # exclude a few common directories in the
+ | \.git # root of the project
+ | \.hg
+ | \.mypy_cache
+ | \.tox
+ | \.venv
+ | _build
+ | buck-out
+ | build
+ | dist
+ )/
+ | docs/build/
+ | node_modules/
+ | venve/
+ | .venv/
+)
+'''
+
+[tool.nbqa.mutate]
+isort = 1
+black = 1
+
+[tool.poetry]
+name = "lekin"
+readme = "README.md" # Markdown files are supported
+version = "0.0.2" # is being replaced automatically
+
+authors = ["Longxing Tan"]
+classifiers = [
+ "Intended Audience :: Developers",
+ "Intended Audience :: Science/Research",
+ "Programming Language :: Python :: 3",
+ "Programming Language :: Python :: 3.7",
+ "Programming Language :: Python :: 3.8",
+ "Programming Language :: Python :: 3.9",
+ "Programming Language :: Python :: 3.10",
+ "Topic :: Scientific/Engineering",
+ "Topic :: Scientific/Engineering :: Mathematics",
+ "Topic :: Scientific/Engineering :: Artificial Intelligence",
+ "Topic :: Software Development",
+ "Topic :: Software Development :: Libraries",
+ "Topic :: Software Development :: Libraries :: Python Modules",
+ "License :: OSI Approved :: MIT License"]
+description = "Flexible job shop scheduler in Python"
+repository = "https://github.com/LongxingTan/python-lekin"
+documentation = "https://python-lekin.readthedocs.io"
+homepage = "https://python-lekin.readthedocs.io"
+
+[tool.poetry.dependencies]
+python = ">=3.7,<3.11"
+#pandas = "^1.1.0"
+matplotlib = "*"
+
+[tool.poetry.dev-dependencies]
+# checks and make tools
+pre-commit = "^2.20.0"
+
+invoke = "*"
+flake8 = "*"
+mypy = "*"
+pylint = "*"
+isort = "*"
+coverage = "*"
+
+# jupyter notebook
+ipykernel = "*"
+black = { version = "*", allow-prereleases = true, extras = ["jupyter"] }
+
+# documentatation
+sphinx = "*"
+pydata-sphinx-theme = "*"
+nbsphinx = "*"
+# pandoc = "*"
+recommonmark = "*"
+ipywidgets = "^8.0.1"
+
+[tool.poetry-dynamic-versioning]
+enable = true
+vcs = "git"
+dirty = false
+style = "semver" # semantic versioning
+
+[build-system] # make the package pip installable
+requires = ["poetry-core>=1.0.7", "poetry-dynamic-versioning>=0.13.1"]
+build-backend = "poetry.core.masonry.api"
diff --git a/setup.cfg b/setup.cfg
new file mode 100644
index 0000000..f0b8151
--- /dev/null
+++ b/setup.cfg
@@ -0,0 +1,69 @@
+[flake8]
+max-line-length = 120
+show-source = true
+ignore =
+ # space before : (needed for how black formats slicing)
+ E203,
+ # line break before binary operator
+ W503,
+ # line break after binary operator
+ W504,
+ # module level import not at top of file
+ E402,
+ # do not assign a lambda expression, use a def
+ E731,
+ # ignore not easy to read variables like i l I etc.
+ E741,
+ # Unnecessary list literal - rewrite as a dict literal.
+ C406,
+ # Unnecessary dict call - rewrite as a literal.
+ C408,
+ # Unnecessary list passed to tuple() - rewrite as a tuple literal.
+ C409,
+ # found modulo formatter (incorrect picks up mod operations)
+ S001,
+ # unused imports
+ F401
+exclude = docs/build/*.py,
+ node_modules/*.py,
+ .eggs/*.py,
+ versioneer.py,
+ venv/*,
+ .venv/*,
+ .git/*
+ .history/*
+
+[isort]
+profile = black
+honor_noqa = true
+line_length = 120
+combine_as_imports = true
+force_sort_within_sections = true
+known_first_party = pytorch_forecasting
+
+[tool:pytest]
+addopts =
+ -rsxX
+ -vv
+ --last-failed
+ --cov=pytorch_forecasting
+ --cov-report=html
+ --cov-config=setup.cfg
+ --cov-report=term-missing:skip-covered
+ --no-cov-on-fail
+ -n0
+testpaths = tests/
+log_cli_level = ERROR
+markers =
+
+[coverage:report]
+ignore_errors = False
+show_missing = true
+
+
+[mypy]
+ignore_missing_imports = true
+no_implicit_optional = true
+check_untyped_defs = true
+
+cache_dir = .cache/mypy/
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_dashboard/__init__.py b/tests/test_dashboard/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_dashboard/test_gantt.py b/tests/test_dashboard/test_gantt.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_datasets/__init__.py b/tests/test_datasets/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/__init__.py b/tests/test_lekin_struct/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/test_job.py b/tests/test_lekin_struct/test_job.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/test_operation.py b/tests/test_lekin_struct/test_operation.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/test_resource.py b/tests/test_lekin_struct/test_resource.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/test_route.py b/tests/test_lekin_struct/test_route.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_lekin_struct/test_timeslot.py b/tests/test_lekin_struct/test_timeslot.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_objective/__init__.py b/tests/test_objective/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/__init__.py b/tests/test_solver/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_construction_heuristics/__init__.py b/tests/test_solver/test_construction_heuristics/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_construction_heuristics/test_lpst.py b/tests/test_solver/test_construction_heuristics/test_lpst.py
new file mode 100644
index 0000000..2435285
--- /dev/null
+++ b/tests/test_solver/test_construction_heuristics/test_lpst.py
@@ -0,0 +1,3 @@
+import unittest
+
+from lekin.solver.construction_heuristics.lpst import LPSTScheduler
diff --git a/tests/test_solver/test_construction_heuristics/test_rule.py b/tests/test_solver/test_construction_heuristics/test_rule.py
new file mode 100644
index 0000000..f6df27e
--- /dev/null
+++ b/tests/test_solver/test_construction_heuristics/test_rule.py
@@ -0,0 +1,3 @@
+import pandas as pd
+
+from lekin.lekin_struct import Job, JobCollector
diff --git a/tests/test_solver/test_construction_heuristics/test_spt.py b/tests/test_solver/test_construction_heuristics/test_spt.py
new file mode 100644
index 0000000..ccb7ab4
--- /dev/null
+++ b/tests/test_solver/test_construction_heuristics/test_spt.py
@@ -0,0 +1,3 @@
+import unittest
+
+from lekin.solver.construction_heuristics.spt import SPTScheduler
diff --git a/tests/test_solver/test_meta_heuristics/__init__.py b/tests/test_solver/test_meta_heuristics/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_meta_heuristics/test_branch_and_bound.py b/tests/test_solver/test_meta_heuristics/test_branch_and_bound.py
new file mode 100644
index 0000000..3a87ac3
--- /dev/null
+++ b/tests/test_solver/test_meta_heuristics/test_branch_and_bound.py
@@ -0,0 +1,26 @@
+from datetime import datetime, timedelta
+import unittest
+
+from lekin.lekin_struct import Job, Operation, Resource, Route, TimeSlot
+from lekin.solver.meta_heuristics.branch_and_bound import BranchAndBoundScheduler
+
+# class BranchAndBoundSchedulerTest(unittest.TestCase):
+# def test_schedule(self):
+# job1 = Job(1, datetime(2023, 1, 10), 2, 1)
+# job2 = Job(2, datetime(2023, 1, 20), 1, 1)
+#
+# op1 = Operation(1, timedelta(hours=2), 2, None, [1])
+# op2 = Operation(2, timedelta(hours=3), None, 1, [1])
+#
+# route1 = Route(1, [op1, op2])
+# print(route1)
+#
+# resource1 = Resource(1, [TimeSlot(datetime(2023, 1, 1), datetime(2023, 1, 3))])
+#
+# job_list = [job1, job2]
+# resource_list = [resource1]
+#
+# scheduler = BranchAndBoundScheduler(job_list, resource_list)
+# schedule = scheduler.get_schedule()
+# for idx, slot in enumerate(schedule):
+# print(f"Job {idx + 1} will start at {slot.start_time} and end at {slot.end_time}")
diff --git a/tests/test_solver/test_meta_heuristics/test_genetic.py b/tests/test_solver/test_meta_heuristics/test_genetic.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_meta_heuristics/test_nsga3.py b/tests/test_solver/test_meta_heuristics/test_nsga3.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_meta_heuristics/test_tabu_search.py b/tests/test_solver/test_meta_heuristics/test_tabu_search.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_reinforcement_learning/__init__.py b/tests/test_solver/test_reinforcement_learning/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_solver/test_reinforcement_learning/test_dqn.py b/tests/test_solver/test_reinforcement_learning/test_dqn.py
new file mode 100644
index 0000000..e69de29
+