摘要
针对柔性工作车间调度问题的特点,设计了基于工序顺序和基于机器分配两种交叉,变异方法对主群体进行传统的遗传操作。并引入病毒群体来感染主群体,将主群体的全局进化和病毒群体的局部进化进行动态结合,克服传统遗传算法早熟和收敛慢的缺点。实验证明此算法的有效性。
To overcome the disadvantages of prematurity and slow convergence in genetic algorithm, a new algorithm is given which combines dynamicly main group＇s overall evolution with virus group＇ s local evolution. According to the characteristic of flexible job shop scheduling the main group＇s evolution is based on two crossover and mutation methods. Then, virus group is inducted to infect main group. scheduling is solved with it. The results show the effectiveness of Finally, the complex problem in flexible job shop the algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2005年第11期1953-1956,共4页
Systems Engineering and Electronics
关键词
柔性工作车间调度
病毒机制
遗传算法
优化
flexible job shop scheduling
vires mechanism
genetic algorithm
optimization
