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: 2011/05/01タイトル(英語): A Constrained Global Optimization Method Based on Multi-Objective Particle Swarm Optimization著者名: 増田 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), Kenzo Kurihara (Kanagawa University)キーワード: 制約条件付き最適化，Particle Swarm Optimization (PSO)，多目的最適化，多目的Particle Swarm Optimization (MOPSO) constrained optimization，particle swarm optimization (PSO)，multi-objective optimization，multi-objective particle swarm optimization (MOPSO)要約(英語): This paper proposes a constrained global optimization method based on Multi-Objective Particle Swarm Optimization (MOPSO). A constrained optimization problem is transformed into another bi-objective problem which minimizes both the original objective function and the total amount of constraint violations. Then, the global optimum of the former problem is obtained as the Pareto optimal solution of the latter one having no constraint violation. In order to find the particular Pareto optimal solution, the proposed method introduces to MOPSO the following operations such as (a) restricting the number of Pareto optimal solutions obtained at each iteration of MOPSO to urge particles to approach the feasible set of the original constrained problem, (b) choosing the most promising Pareto optimal solution as the global best solution so as to exclude solutions dominated by it, and (c) encouraging to add Pareto optimal solutions if the number of them is too small to recover the diversity of search. Numerical examples verify the effectiveness, efficiency and wide applicability of the proposed method. For some famous engineering design problems, in particular, it can find solutions which are comparative to or better than the previously known best ones.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.131 No.5 （2011） 特集：メタヒューリスティクスとその応用本誌掲載ページ: 990-999 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/131/5/131_5_990/_article/-char/ja/
