2306 制約条件の感度解析と多目的PSOとの複合型アルゴリズム(OS6-2 設計と最適化II-多目的最適化-,OS6 設計と最適化)

概要

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A multi-objective particle swarm optimization (MOPSO) is known as a multipoint-search-based meta-heuristic approach to find diverse Pareto solutions efficiently, but has difficulty to handle the constraint conditions. Overcoming the disadvantage, this study proposes a hybrid algorithm incorporating MOPSO and sensitivity analysis on constrained conditions. When the design candidate is violated, the design candidate is moved to feasible domain based on the gradient information of the constraint conditions. The transerring algorithm is adopted for each design candidate at each iteration in MOPSO algorithms. Through several numerical examples, the diversity and convergency of the Pareto solutions and the performance of the proposed method are investigated.
一般社団法人日本機械学会の論文
2011-10-21