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.
作者
唐艺军
李雪
TANG Yijun;LI Xue(College of Business Administration,Liaoning Technical University,Huludao 125105,China)
出处
《现代制造工程》
CSCD
北大核心
2023年第10期8-14,共7页
Modern Manufacturing Engineering
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
flexible job-shop scheduling
Genetic Algorithm(GA)
simulated annealing algorithm
Levy flight
