Multi-Point Combinatorial Optimization Method Utilizing Expanded Search Mechanism Based on Hierarchical Interpretation in Solution Space

カテゴリ: 部門大会

論文No: SS3-9

グループ名: 【C】2019年電気学会電子・情報・システム部門大会プログラム

発行日: 2019/08/28

タイトル(英語): Multi-Point Combinatorial Optimization Method Utilizing Expanded Search Mechanism Based on Hierarchical Interpretation in Solution Space

著者名: 李 絮元(首都大学東京),田村 健一(首都大学東京),土屋 淳一(首都大学東京),安田 恵一郎(首都大学東京)

著者名(英語): Xuyuan Li|Kenichi Tamura|Junichi Tsuchiya|Keiichiro Yasuda

キーワード: 組合せ最適化|メタヒューリスティクス|探索機構|集中化|多様化|Combinatorial Optimization|Metaheuristics|Search Mechanism|Intensification|Diversification

要約(日本語): In this paper, we introduce a new expanded search mechanism, which is paying attention to updating the group of solutions searched by a same point rather than just a solution. Using this mechanism in multi-point searching, every search point can form a nonoverlapping searched area in solution space of neighborhood relationship, which can solve issues when using common search mechanism. Basing on the high affinities to “Hierarchical Interpretation of Solution Space”, which is also proposed by our research group, we utilize the expanded search mechanism to construct a search tactic among macroscopic movement. And basing on this assembly, we propose a new combinatorial optimization method to verify the basic performance of the expanded search mechanism.

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