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

DOI Web Site Web Site 被引用文献2件 参考文献40件
  • Hao Xinchang
    Graduate School of Information, Production and Systems, Waseda University
  • Lin Hao Wen
    Harbin Institute of Technology Shenzhen Graduate School
  • Chen Xili
    Graduate School of Information, Production and Systems, Waseda University
  • Murata Tomohiro
    Graduate School of Information, Production and Systems, Waseda University

この論文をさがす

抄録

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.

収録刊行物

被引用文献 (2)*注記

もっと見る

参考文献 (40)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ