具有平行批处理机的多目标FJSP问题研究
Research on Multi-objective FJSP Problem with Parallel Batch Processing Machines
宋立波 1刘昶 2史海波2
作者信息
- 1. 中国科学院网络化控制系统重点实验室,辽宁 沈阳 110016;中国科学院沈阳自动化研究所,辽宁 沈阳 110016;中国科学院机器人与智能制造创新研究院,辽宁 沈阳 110016;中国科学院大学,北京 100049
- 2. 中国科学院网络化控制系统重点实验室,辽宁 沈阳 110016;中国科学院沈阳自动化研究所,辽宁 沈阳 110016;中国科学院机器人与智能制造创新研究院,辽宁 沈阳 110016
- 折叠
摘要
针对具有平行批处理机的多目标柔性作业车间调度问题,建立以最大完工时间、最大机器负荷和能耗为优化目标的数学模型,并提出了一种多种群MOEAD算法进行求解.算法结合了多种群策略的优势,三个子种群分别采用了WS、TE和BI三种聚合函数进行协同搜索,保持种群多样性的同时扩展了算法的搜索广度.设计了符合问题特性的进化算子和局部搜索策略,提高算法整体搜索性能.通过标准的FJSP算例和符合问题特性的实际数据,验证了所提算法的可行性与有效性.
Abstract
A mathematical model was established for the multi-objective flexible job shop scheduling problem with parallel batch processing machines,with maximum completion time,maximum machine load,and energy con-sumption as optimization objectives.A multi group MOEAD algorithm was proposed in the paper for solution.The al-gorithm combined the advantages of multiple-population strategies,and the three sub-populations used three aggrega-tion functions of WS,TE and BI for collaborative search,which maintains the diversity of the population while expan-ding the search breadth of the algorithm.An evolutionary operator and a local search strategy were designed in line with the characteristics of the problem to improve the overall search performance of the algorithm.The feasibility and effectiveness of the proposed algorithm were verified by standard FJSP examples and actual data that meet the charac-teristics of the problem.
关键词
柔性作业车间/平行批处理机/绿色调度Key words
Flexible job shop/Parallel batch processing machines/Green scheduling引用本文复制引用
基金项目
辽宁省重点研发计划(2020JH2/10100039)
出版年
2024
NETL
NSTL
万方数据