Cooperative Bayesian Optimization Algorithm: a Novel Approach to Multiple Resources Scheduling Problem

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: 2012/12/01

タイトル(英語): Cooperative Bayesian Optimization Algorithm: a Novel Approach to Multiple Resources Scheduling Problem

著者名: Xinchang Hao (Graduate School of Information, Production and Systems, Waseda University), Hao Wen Lin (Harbin Institute of Technology Shenzhen Graduate School), Xili Chen (Graduate School of Information, Production and Systems, Waseda University), Tomohir

著者名(英語): Xinchang Hao (Graduate School of Information, Production and Systems, Waseda University), Hao Wen Lin (Harbin Institute of Technology Shenzhen Graduate School), Xili Chen (Graduate School of Information, Production and Systems, Waseda University), Tomohiro Murata (Graduate School of Information, Production and Systems, Waseda University)

キーワード: Bayesian network，Estimation of distribution algorithm，Multiple resources scheduling，Co-evolutionary algorithm

要約(英語): During the past several years, there has been a significant number of researches conducted in the field of Multiple Resources Scheduling Problem (MRSP). Intelligent manufacturing planning and scheduling based on meta-heuristic methods, such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Particle Swarm Optimization (PSO), have become some of the common tools for finding acceptable solutions within reasonable computational time in real settings. However, limited researches were conducted at analysing the effects of interdependent relationships between each activity of group decision-making processes. Moreover for a complex and large problem, local constraints and objectives from each managerial entity, and their effects on global objectives of the problem cannot be effectively represented using a single model. In this paper, we propose a novel Cooperative Bayesian Optimization Algorithm (COBOA) to overcome the challenges mentioned afore. The COBOA approach employs the concepts of divide-and-conquer strategy and it is incorporated with an innovative co-evolutionary framework. Considerable experiments were performed, and the results confirmed that COBOA outperforms recent research results for scheduling problems in FMS.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.132 No.12 （2012） 特集：電気関係学会東海支部連合大会

本誌掲載ページ: 2007-2018 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/132/12/132_2007/_article/-char/ja/