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

Authors :
Gong, Qingshan
Li, Junlin
Jiang, Zhigang
Wang, Yan
Source :
Engineering Applications of Artificial Intelligence. Mar2024, Vol. 129, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09521976
Volume :
129
Database :
Academic Search Index
Journal :
Engineering Applications of Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
175410884
Full Text :
https://doi.org/10.1016/j.engappai.2023.107595