スカラー化とParticle Swarm Optimizationを併用した簡便な進化型多目的最適化手法の設計
スカラー化とParticle Swarm Optimizationを併用した簡便な進化型多目的最適化手法の設計
カテゴリ: 論文誌(論文単位)
グループ名: 【C】電子・情報・システム部門
発行日: 2012/01/01
タイトル(英語): A Design of a Simple Evolutionary Multi-objective Optimization Method Based on the Combined Use of Scalarization and Particle Swarm Optimization
著者名: 増田 和明(神奈川大学),原田 和明(神奈川大学),栗原 謙三(神奈川大学)
著者名(英語): Kazuaki Masuda (Kanagawa University), Kazuaki Harada (Kanagawa University), Kenzo Kurihara (Kanagawa University)
キーワード: 多目的最適化,パレート最適集合,拡大Tchebycheffスカラー化,Particle Swarm Optimization (PSO) multi-objective optimization,Pareto optimal set,augmented Tchebycheff scalarization,Particle Swarm Optimization (PSO)
要約(英語): This paper proposes a general methodology of multi-objective optimization based on the combined use of scalarization and evolutionary computation approaches. Mathematically, it is guaranteed that a Pareto optimal solution of a multi-objective optimization problem (MOP) can be found by minimizing the corresponding augmented Tchebysheff scalarized function. In this way, different Pareto optimal solutions can be obtained by solving different single-objective optimization problems (SOPs) with different weight for scalarization. Aiming at knowing the global structure of Pareto optimal set and/or Pareto frontier of a MOP with simple computation, we propose the basic concept that, (a) the SOPs with different weight should be solved independently by some evolutionary computation algorithms; and, (b) previously obtained useful solutions should be partly reused for the optimization of another SOP. In particular, for continuous-variable MOPs, we also propose a practical computation method based on the concept, which uses Particle Swarm Optimization (PSO) with effective reinitialization mechanism. The usefulness of the proposed methodology is demonstrated through numerical experiments with the proposed computation method.
本誌: 電気学会論文誌C(電子・情報・システム部門誌) Vol.132 No.1 (2012) 特集:確率的最適化と機械学習の統計的設計と応用
本誌掲載ページ: 42-52 p
原稿種別: 論文/日本語
電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/132/1/132_1_42/_article/-char/ja/
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