stochastic-investment-planning

This is a implementation of a two-stage stochastic model used for investment planning under uncertainity. The modified problem is taken from [1]. This particual problem originally appeared in [2]. The problem is first implemented as a determinestic linear program using and later solved using mpi-sppy.

Files and Folders

• 📁 'run_me.ipynb' - The main Jupyter Noteboomk file which solves the problem with explanations
• 📁 'helper_function.py' - Python file containing all necessary functions required to run 'run_me.ipynb'
• 📁 'requirements.txt' - List of required packages for running the code, that can be downloaded directly using

Installation

The repository can be cloned to the local computer manually or using the following code:

git clone https://github.com/nkpanda97/stochastic-investment-planning

The required packages can be installed dorectly using 'requirements.txt' file in using the following command:

$ conda create --name <env> --file <this file>
$ platform: osx-64

References

[1] Klein Haneveld, W. K., van der Vlerk, M. H., & Romeijnders, W. (2020). Stochastic Programming. In Graduate Texts in Operations Research. Springer International Publishing. https://doi.org/10.1007/978-3-030-29219-5
[2] F.V. Louveaux and Y. Smeers. Optimal investments for electricity generation: a stochastic model and a test problem. In Yu. Ermoliev and R.J-B. Wets, editors, Numerical techniques for stochastic optimization, chapter 24, pages 445–453. Springer-Verlag, Berlin, 1988.