During the past several years, there has been a significant amount of research conducted simultaneous multiple resources scheduling problem (SMRSP) Intelligence manufacturing based on meta-heuristics, such as genetic algorithms (GAs), simulated annealing (SA) particle swarm optimization(PSO), has become a common tool to find satisfactory solutions within reasonable computational times in real settings. However, there are few researches considering interdependent relation during the decision activities, moreover for complex and large problems, local constraints and objectives from each managerial entity cannot be effectively represented in a single model for complex and large problems. In this paper, we propose a novel cooperative Bayesian optimization algorithm (COBOA) undertaking divide-and-conquer strategy and co-evolutionary framework. Considerable experiments are conducted and the results confirmed that COBOA outperforms recent researches for the scheduling problem in FMS.
|出版ステータス||Published - 2011 12月 1|
|イベント||2011 2nd International Conference on Innovations in Bio-inspired Computing and Applications, IBICA 2011 - Shenzhen, Guangdong, China|
継続期間: 2011 12月 16 → 2011 12月 18
|Conference||2011 2nd International Conference on Innovations in Bio-inspired Computing and Applications, IBICA 2011|
|Period||11/12/16 → 11/12/18|
ASJC Scopus subject areas
- コンピュータ サイエンスの応用