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High-Dimensional Expensive Multiobjective Optimization Using a Surrogate-Assisted Multifactorial Evolutionary Algorithm

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YNU-NakataLab/SFA-MFDE

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SFA/MFDE

-This is an open source code of SFA/MFDE implemented by MATLAB.

-You can easily use this code on Evolutionary multi-objective optimization platform (PlatEMO) on MATLAB.

How to run

  1. Download PlatEMO from here.

  2. Add SFA/MFDE source code to "Algorithms/Multi-objective optimization".

  3. Run "platemo.m" and select SFA/MFDE on GUI.

  4. Determine the experimental settings and push "Start" button.

Copyright

The Copyright of the SFA/MFDE belongs to the Nakata Lab from Yokohama National University, Japan. You are free to use this code for research purposes. Please refer the following article: "Yuma Horaguchi, Masaya Nakata, High-Dimensional Expensive Multiobjective Optimization Using a Surrogate-Assisted Multifactorial Evolutionary Algorithm, The Genetic and Evolutionary Computation Conference (GECCO), ACM, July 2025, 572-580".

@inproceedings{horaguchi2025high,
  title={{High-Dimensional Expensive Multiobjective Optimization Using a Surrogate-Assisted Multifactorial Evolutionary Algorithm}},
  author={Horaguchi, Yuma and Nakata, Masaya},
  booktitle={The Genetic and Evolutionary Computation Conference (GECCO)},
  pages={572--580},
  month={July},
  year={2025},
  publisher={ACM},
  doi={10.1145/3712256.3726483}
}

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High-Dimensional Expensive Multiobjective Optimization Using a Surrogate-Assisted Multifactorial Evolutionary Algorithm

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