An Improved MOEA/D-DE with Bilayered Decomposition for Difficult Constrained Multi-objective Optimization

カテゴリ: 部門大会

論文No: SS2-5

グループ名: 【C】2024年電気学会電子・情報・システム部門大会

発行日: 2024/08/28

タイトル(英語): An Improved MOEA/D-DE with Bilayered Decomposition for Difficult Constrained Multi-objective Optimization

著者名: Yasuda Yusuke（Tokyo Metropolitan University）,Tamura Kenichi（Tokyo Metropolitan University）,Yasuda Keiichiro（Tokyo Metropolitan University）

著者名(英語): Yusuke Yasuda (Tokyo Metropolitan University),Kenichi Tamura (Tokyo Metropolitan University),Keiichiro Yasuda (Tokyo Metropolitan University)

キーワード: constrained multi-objective optimization|MOEA/D|differential evolution|constraint handling|decomposition|constrained multi-objective optimization|MOEA/D|differential evolution|constraint handling|decomposition

要約(日本語): The multiobjective evolutionary algorithm based on decomposition with a differential evolution operator (MOEA/D-DE) is effective for unconstrained multi-objective optimization problems with complex Pareto fronts. However, in constrained multi-objective optimization problems (CMOPs), conflicts arise not only between objectives but also between objectives and constraints. Therefore, we propose a method combining MOEA/D-DE with bilayered decomposition. Experiments demonstrate that the proposed algorithm outperforms conventional ones in challenging CMOPs.