基于改进混合遗传算法的柔性车间调度问题研究  

Research on flexible shop floor scheduling problem based on improved hybrid genetic algorithm

作　　者：唐艺军[1] 李雪[1] TANG Yijun;LI Xue(College of Business Administration,Liaoning Technical University,Huludao 125105,China)

机构地区：[1]辽宁工程技术大学工商管理学院,葫芦岛125105

出　　处：《现代制造工程》2023年第10期8-14,共7页Modern Manufacturing Engineering

摘　　要：针对柔性作业车间调度问题,提出了一种将模拟退火算法和莱维(Levy)飞行扰动策略引入传统遗传算法(Genetic Algorithm,GA)的改进混合遗传算法。基于传统遗传算法,增加了自适应交叉概率和变异概率,生成初始种群后,对优秀个体进行保护,对性能较差的个体进行模拟退火和Levy飞行操作,克服了传统遗传算法的“早熟”和易陷入局部最优解的问题。通过仿真对比实验的测试,证明了该算法的有效性和优越性。For the flexible job-shop scheduling problem,an improved hybrid Genetic Algorithm(GA) that introduces simulated annealing algorithm and Levy flight perturbation strategy to the traditional genetic algorithm is proposed.Based on the traditional genetic algorithm,adds adaptive crossover probability and variation probability,generates the initial population,protects the good individuals,and simulates annealing and Levy flight operation for the poor performers,which overcomes the problems of “premature” and easy to fall into the local optimal solution of the traditional genetic algorithm.The effectiveness and superiority of the algorithm are proved by simulated comparison experiments.

关 键 词：柔性作业车间调度 遗传算法 模拟退火算法 莱维飞行 

分 类 号：TH165[机械工程—机械制造及自动化]