【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.更多还原

【Abstract】 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.更多还原