计算机应用研究2023，Vol.40Issue(12)：3690-3695,6.DOI:10.19734/j.issn.1001-3695.2022.10.0546
改进混合多目标蚁群算法求解带运输时间和调整时间的柔性作业车间调度问题
Improved hybrid multi-objective ant colony optimization for flexible Job-Shop scheduling problem with transportation time and setup time
摘要
Abstract
Flexible job shop scheduling is an important combinatorial optimization problem.In the actual production process,there are transportation time and setup time in indirect processing activities such as product handling,and machine tool chan-ging,which will affect the production cycle.This paper studied the flexible job shop scheduling problem considering both trans-portation time and setup time,established a mathematical model with the objectives of minimizing the maximum completion time,total workload,the workload of the critical machine,and penalties of earliness/tardiness,and proposed an improved hybrid multi-objective ant colony optimization.It designed a distributed coding method by combining the problem characteristics and al-gorithm features,using an improved ant colony optimization to search for the optimal scheduling solution for each optimization ob-jective separately,performing non-dominated sorting selection for the set of scheduling solutions,and proposing mutation and closeness operations in order to improve the search accuracy of the algorithm.Finally,it conducted simulation experiments using benchmark and production instance and compared them with the improved genetic algorithm and MOGATS algorithm,and the ex-perimental results showed that the proposed improved hybrid multi-objective ant colony optimization is effective and feasible.关键词
改进蚁群算法/运输时间/调整时间/柔性作业车间调度问题Key words
improved ant colony optimization/transportation time/setup time/flexible job shop scheduling problem分类
机械制造引用本文复制引用
张国辉,闫少峰,陆熙熙,张海军..改进混合多目标蚁群算法求解带运输时间和调整时间的柔性作业车间调度问题[J].计算机应用研究,2023,40(12):3690-3695,6.基金项目
国家自然科学基金资助项目(U1904167) （U1904167）
河南省高校科技创新团队(21IRTSTHN018) （21IRTSTHN018）
郑州航院研究生教育创新计划基金资助项目(2022CX22) （2022CX22）
