摘要
置换流水车间调度问题(permutation flow shop scheduling problem,PFSP)广泛存在于流程和离散制造企业。本文提出一种改进的Jaya算法求解最小化最大完工时间为目标的PFSP。在改进Jaya算法中,设计了基于最优和最差个体的4种个体更新方案,通过4种邻域结构对个体进行局部搜索,并通过多样性控制策略来保证种群的多样性。采用改进Jaya算法分解求解Car、Rec和Taillard基准问题,并与其他算法进行比较,验证了所提算法的有效性。
Permutation flow shop scheduling problem is widely applied in process and discrete manufacturing enterprises.An improved Jaya algorithm is proposed to solve the PFSP with the minimum makespan.In the improved Jaya algorithm,four individual updating schemes based on the best and the worst individuals are proposed,and local search for individuals is carried out through four neighborhood structures.Diversity control strategy is applied to ensure the diversity of population.The improved Jaya algorithm is used to solve the Car,Rec and Taillard benchmark instances,and the experimental results validate the effectiveness of the proposed algorithm.
作者
刘梦伊
薛燕社
马思奕
张超勇
LIU Mengyi;XUE Yanshe;MA Siyi;ZHANG Chaoyong(Business School of Hohai University,Nanjing 211100,China;School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《工业工程》
北大核心
2022年第3期141-150,共10页
Industrial Engineering Journal
基金
国家自然科学基金资助项目(51875429)
广东省重点领域研发计划资助项目(2019B090921001)。
