Hybrid Mean Particle Swarm Optimization Algorithm for Permutation Flow Shop Scheduling Problem

摘要：

　　This paper presents a new hybrid mean particle swarm optimization algorithm with improved NEH heuristic approach and local search strategies by using an immune mechanism.This hybrid mean particle swarm optimization algorithm is used for permutation flow shop scheduling problems.Finally,twenty-five problems are used to test the performance of the algorithm,the experimental results show that the proposed approach is an effective and practical.

关键词： Mean particle swarm optimization Permutation flow shop scheduling NEH heuristic Immune algorithm Pairwise

作者: Yongquan Zhou Zhengxin Huang Yanlian Du Qiaoqiao Gong

作者单位: College of Mathematics and Computer Science, Guangxi University for Nationalities Nanning, Guangxi 530006, China

会议类型: 国际会议

会议名称: the 2010 International Conference on Frontiers of Manufacturing and Design Science(第一届制造与设计科学国际会议(ICFMD 2010))

会议地点: 重庆

会议语种:英文

页码: 270-274

在线出版日期: 2010-12-11（万方平台首次上网日期，不代表论文的发表时间）