A hierarchical integration scheduling method for flexible job shop with green lot splitting

被引:24
作者
Gong, Qingshan [1 ]
Li, Junlin [1 ]
Jiang, Zhigang [1 ,2 ]
Wang, Yan [3 ]
机构
[1] Hubei Univ Automot Technol, Shiyan 442002, Peoples R China
[2] Wuhan Univ Sci & Technol, Key Lab Met Equipment & Control Technol, Wuhan 430081, Peoples R China
[3] Univ Brighton, Dept Comp Engn & Math, Brighton BN24GJ, England
基金
中国国家自然科学基金;
关键词
Green scheduling; Lot splitting; Flexible job shop; Hierarchical optimization; Production planning and scheduling; OPTIMIZATION METHOD; ALGORITHM; SEQUENCE;
D O I
10.1016/j.engappai.2023.107595
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The integration of green scheduling and lot splitting scheduling is indispensable for ensuring the coordinated optimization of economic and environmental benefits in flexible job-shop scheduling (FJS). However, this integration involves not only the indicator of greenness and economy but also the process of production planning and scheduling, which is substantially complicated. To this end, a hierarchical integrated scheduling method is proposed by comprehensively considering the multilevel organizational structure and task configuration characteristics of flexible job-shop, as well as the differences in objectives on different scheduling levels: workshop level, process unit level, machine tool level. On the workshop level, a lot splitting model is presented to obtain the optimal processing task set for each production cycle with the minimum expected cost (startup cost, tardiness cost, and holding cost). On the process unit level, a task allocation model is given to allocate the optimal workload for each machine tool with the minimum processing energy consumption and maximum machine load. On the machine tool level, an operation sequencing model is established to obtain the optimal processing sequence for each machine tool with the minimum standby energy consumption and makespan. According to the solving characteristics of the hierarchical models, a multi-objective algorithm is applied. Finally, a case study is demonstrated to validate the proposed method.
引用
收藏
页数:11
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