SADE-ATDSC

Surrogate-assisted Differential Evolution with Adaptation of Training Data Selection Criterion

• This is an open-source code of SADE-ATDSC implemented by MATLAB.

• All codes are our originals and implemented to run on PlatEMO.

How to run

1. Download all the files of SADE-ATDSC and PlatEMO.

2. Add the SADE-ATDSC directory in this repository to the Algorithms/Single-objective optimization directory.

3. Run platemo.m and select SADE-ATDSC. See the documents of PlatEMO for more details.

Copyright

The copyright of the SADE-ATDSC belongs to authors in the Evolutionary Intelligence Research Group (Nakata Lab) at Yokohama National University, Japan. You are free to use this code for research purposes. Please refer to the following article;

Kei Nishihara and Masaya Nakata, “Surrogate-assisted Differential Evolution with Adaptation of Training Data Selection Criterion,” in IEEE Symp. Ser. Comput. Intell. (SSCI), Dec. 2022, pp. 1675–1682.

@inproceedings{nishihara2022surrogate,
  title      = "{Surrogate-assisted Differential Evolution with Adaptation of
                Training Data Selection Criterion}",
  booktitle  = "{IEEE Symp. Ser. Comput. Intell. (SSCI)}",
  author     = "Nishihara, Kei and Nakata, Masaya",
  pages      = "1675--1682",
  month      =  dec,
  year       =  2022,
  conference = "2022 IEEE Symposium Series on Computational Intelligence (SSCI)",
  doi        = "10.1109/SSCI51031.2022.10022105"
}