基于混合遗传算法的作业车间调度问题的研究与仿真

作业车间调度问题(JSP)是一类典型的NP-hard问题,遗传算法(GA)由于其隐合并行性和全局解空间搜索两大优点而成为解决JSP问题的常用工具.但是,由于JSP问题本身的特点,普通遗传算法难以在解此类问题时得到满意解,最突出的问题就是过早收敛于某一局部最优解,使算法效率降低.在此基础上,将遗传算法和模拟退火算法相结合,提出了一种基于遗传和模拟退火的混合算法,该算法将模拟退火算法赋予搜索过程时变性融入其中,具有明显的概率跳跃性,并选取了典型问题进行分析和仿真研究.仿真结果表明,与传统的遗传算法相比该方法是行之有效的.

Job-shop Scheduling Problem Based on Hybrid Genetic Algorithm

A new hybrid algorithm based on genetic algorithm and simulated annealing is proposed in this paper,in which the algorithm of simulated annealing algorithm is given with a time-varying characteristical to integrate insearching process,which show the algorithm with a marked probability-jump.Meanwhile, by analyzing typical problems,the algorithm is studied through simulation.The results prove that this method is feasible and effective compared with traditional genetic algorithm.