実行可能化演算を組み込んだ進化計算アルゴリズムによる制約条件付き最適化手法

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: 2014/09/01

タイトル(英語): Constrained Optimization Methods Using Evolutionary Algorithms with an Additional Use of Feasibilization Operations

著者名: 増田　和明（神奈川大学工学部）

著者名(英語): Kazuaki Masuda (Faculty of Engineering, Kanagawa University)

キーワード: 制約条件付き最適化，進化計算アルゴリズム，実行可能化，粒子群最適化 (Particle Swarm Optimization, PSO)，差分進化 (Differential Evolution, DE)　　constrained optimization，evolutionary algorithm，feasibilization，particle swarm optimization (PSO)，differential evolution (DE)

要約(英語): We propose a simple but useful concept of the constrained optimization using evolutionary algorithms. In conventional constraint-handling approaches, it is desired that the objective and constraints should be improved simultaneously. In contrast, in the proposed approach, with an additional use of feasibilization operations to all new solutions, a constrained problem can virtually be recognized as an unconstrained one and the objective function can be improved only in the feasible region. The feasiblization operation is realized by solving a set of nonlinear equations regarding constraints. Nevertheless, in case of possible failure of feasibilization due to limitations of nonlinear solvers, the idea of ε level comparison is applied to evaluate solutions. We also propose two practical algorithms: Feasibilization Particle Swarm Optimization (FPSO) and Feasibilization Differential Evolution (FDE). We show the usefulness of the proposed method by numerical experiments; in particular, both of them perform as well as or better than existing promising methods for engineering design problems.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.9 （2014） 特集Ⅰ：制御系設計における適応・学習・同定・モデリングの新展開　特集Ⅱ：インテリジェント・システム

本誌掲載ページ: 1333-1340 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/134/9/134_1333/_article/-char/ja/