An effective hybrid optimization algorithm for the flow shop scheduling problem

摘要：

This paper presents a new multi-swarm co-evolutionary algorithm named parallel particle swam optimization (PPSO) on the basis of standard PSO algorithm. Simulated annealing (SA) algorithm was introduced to increase escaping probability from local optima. By reasonably combining the PPSO with SA, we develop a general, fast and easily implemented hybrid optimization algorithm, and apply it to solve flow shop scheduling problem. Comparing results indicate that the new hybrid method is an effective and competitive approach for the flow shop scheduling problem.

关键词： Parallel particle swarm optimization Simulated annealing Hybrid optimization algorithm Flow shop scheduling problem

作者: Sun Kai Yang Genke

作者单位: Department of Automation, Shanghai Jiao Tong University Shanghai 200030, P. R. China

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 1234-1238

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）