一种求解柔性工作车间调度问题的混合遗传算法  

A hybrid genetic algorithm for flexible job shop scheduling problem

作　　者：宋莉波[1] 徐学军[1] 孙延明[1] 查靓[1] 

机构地区：[1]华南理工大学工商管理学院,广州510640

出　　处：《管理科学学报》2010年第11期49-54,共6页Journal of Management Sciences in China

基　　金：国家自然科学基金资助项目(71071059);国家自然科学基金资助项目(70872031);教育部"新世纪优秀人才支持计划"资助项目(NCET-08-0212)

摘　　要：针对柔性工作车间调度问题(Flexible job-shop scheduling problem,FJSP),提出了一种基于混合遗传算法的求解方案,在初始种群中引入基于启发式规则生成的优良个体,并使用有效的交叉、变异算子避免不可行个体的产生,同时利用混沌序列的随机性和遍历性特点,在遗传进化的过程中增加基于混沌序列的邻域搜索功能,以提高遗传算法的执行效率.通过仿真实验验证了该算法的可行性和有效性.A genetic algorithm combined with local search is proposed to solve the FJSP with MAKESPAN criterion.A small percentage of elitist individuals are introduced into the initial population to fasten GA＇s convergence speed,efficient crossover and mutation operators are adopted to avoid infeasible solutions and to hasten the emergency of optimum solution.During the local search process,Logistic chaotic sequence is adopted to explore better neighborhood solutions around the best individual of the current generation.Representative flexible job shop scheduling benchmark problems are solved in order to test the feasibility and validity of the proposed algorithm.

关 键 词：柔性工作车间调度问题 混沌 混沌序列 遗传算法 

分 类 号：C934[经济管理—管理学]