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High-Dimensional Expensive Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction

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DR-MCEA-D

-This is an open source code of DR-MCEA/D 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 DR-MCEA/D source code to "Algorithms/Multi-objective optimization".

  3. Run "platemo.m" and select DR-MCEA/D on GUI.

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

Copyright

The Copyright of the DR-MCEA/D 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 Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction, 2023 62nd Annual Conference of the Society of Instrument and Control Engineers (SICE), IEEE, September 2023, 1535-1542".

@inproceedings{horaguchi2023high,
  title={{High-Dimensional Expensive Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction}},
  author={Horaguchi, Yuma and Nakata, Masaya},
  booktitle={2023 62nd Annual Conference of the Society of Instrument and Control Engineers (SICE)},
  pages={1535--1542},
  month={September},
  year={2023},
  publisher={IEEE}
  doi={10.23919/SICE59929.2023.10354103}
}

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High-Dimensional Expensive Optimization by Classification-based Multiobjective Evolutionary Algorithm with Dimensionality Reduction

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