混合粒子群算法求解作业车间调度问题  

Hybrid particle swarm optimization for solving job-shop scheduling problem

作　　者：刘凤杰 薛仁政[1] LIU Fengjie;XUE Renzheng(School of Computer and Control Engineering,Qiqihar University,Qiqihar 161006,China)

机构地区：[1]齐齐哈尔大学计算机与控制工程学院,黑龙江齐齐哈尔161006

出　　处：《高师理科学刊》2022年第6期38-43,共6页Journal of Science of Teachers＇College and University

基　　金：黑龙江省省属高等学校基本科研业务费科研项目(135409224)。

摘　　要：针对最小化完工时间的作业车间调度问题,提出混合的粒子群优化算法.针对作业车间调度中随机交换2个工件邻域变换存在盲目性,采用机器空闲时间的关键工序邻域搜索算法,结合粒子群算法收敛速度快和遗传算法变异操作增加全局搜索能力的优点,将2种算法结合.通过标准JSP问题测试库验证了算法的有效性.Aiming at the job-shop scheduling problem of minimizing completion time,a hybrid particle swarm optimization algorithm is proposed.Aiming at the blindness of neighborhood transformation of randomly exchanging two workpieces in job-shop scheduling,the key process neighborhood search algorithm of machine idle time is adopted.Combined with the advantages of fast convergence speed of particle swarm optimization algorithm and mutation operation of genetic algorithm to increase the global search ability,the two algorithms are combined.The effectiveness of the algorithm is verified by the standard JSP problem test library.

关 键 词：粒子群算法 车间调度 关键路径 邻域搜索 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]