信息与控制2012，Vol.41Issue(2)：193-196,209,5.DOI:10.3724/SP.J.1219.2012.00193
求解车间调度问题的2阶段混合粒子群优化算法
A Two Stage Hybrid Particle Swarm Optimization Algorithm for Job-Shop Scheduling Problem
摘要
Abstract
A two-stage hybrid particle swarm optimization (TS-HPSO) algorithm is proposed to solve the job-shop scheduling problem. In the first phase, the inertia coefficient w is set bigger and the ability of social learning of particles is removed so that each particle can search the local area fully. In the second phase, the initial particles are initialized according to the best position of each particle searched in the first phase, and at the same time, the mutation operation of genetic algorithm is used to ensure the diversity of particles. A neighborhood based random greedy search is performed on the best particle gbest to ensure the optimization of the algorithm. The computational results show the effectiveness of the algorithm.关键词
粒子群算法/车间作业调度问题/最小化完工时间/变异Key words
particle swarm optimization/ job-shop scheduling problem/ minimized makespan/ mutation分类
信息技术与安全科学引用本文复制引用
宋存利,时维国..求解车间调度问题的2阶段混合粒子群优化算法[J].信息与控制,2012,41(2):193-196,209,5.基金项目
辽宁省教育厅计划资助项目 (L2010086). （L2010086）
