A Hybrid Particle Swarm Optimization Method for Permutation Flow Shop Scheduling Problem

摘要：

　　The Permutation Flow Shop Scheduling Problem(PFSP)is a typical example in Production Scheduling,which has attracted many researchers attention.This paper takes to the advantage of the swarm characteristic of Particle Swarm optimization(PSO)algorithm to find the best particle in the solution space.The objective is to minimize the makespan.Firstly,the initial solution of the algorithm is generated by the famous heuristic NEH algorithm.The NEH algorithm was used to initialize the particle of global extreme values.Secondly,we take some optimized strategy to set the parameters,acceleration constant and nonlinear inertia weight strategy which based on random self-adaptively by means of chaos method for setting parameters.These optimized methods can avoid algorithm to be trapped in local optimum.At last,simulated results demonstrate that the hybrid PSO method is feasible and effective for the PFSP.

关键词： Permutation Flow Shop Scheduling Problem Particle Swarm Optimization NEH Algorithm Makespan

作者: Lin Wang Jianhua Qu Yuyan Zheng

作者单位: School of Management Science and Engineering,Shandong Normal University,Jinan,China

会议类型: 国际会议

会议名称: The 9th International Conference on Pervasive Computing and Application(ICPCA 2014)(第九届全国普适计算学术会议、第九届全国人机交互联合学术会议)

会议地点: 南昌

会议语种:英文

页码: 1-12

在线出版日期: 2013-09-26（万方平台首次上网日期，不代表论文的发表时间）