Optimizing distributed reentrant heterogeneous hybrid flowshop batch scheduling problem: Iterative construction-local search-reconstruction algorithm

•A MILP model for the DRHHFBSP is developed.•A construction heuristic capable of generating excellent solutions is developed.•An iterative construction-local search-reconstruction algorithm is designed. In recent years, the distributed hybrid flowshop scheduling problem (DHFSP) has garnered widespre...

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Bibliographic Details
Published in:Swarm and evolutionary computation Vol. 90; p. 101681
Main Authors: He, Peng, Zhang, Biao, Lu, Chao, Meng, Lei-lei, Zou, Wen-qiang
Format: Journal Article
Language:English
Published: Elsevier B.V 01.10.2024
Subjects:
Batch scheduling
Distributed hybrid flowshop scheduling
Heuristic
Reentrant scheduling
Distributed hybrid flowshop scheduling
Batch scheduling
Reentrant scheduling
Heuristic
ISSN:2210-6502
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Summary:•A MILP model for the DRHHFBSP is developed.•A construction heuristic capable of generating excellent solutions is developed.•An iterative construction-local search-reconstruction algorithm is designed. In recent years, the distributed hybrid flowshop scheduling problem (DHFSP) has garnered widespread attention due to the continuous emergence of practical challenges. The production model, characterized by multiple varieties and small batches, is widely observed in the industrial sector. Additionally, in various real-world scenarios, batches often undergo repeated processes across multiple stages. This paper addresses the research gap by introducing the reentrant nature of batches and the heterogeneity of factories into the DHFSP, resulting in a novel problem referred to as the distributed reentrant heterogeneous hybrid flowshop batch scheduling problem (DRHHFBSP). To tackle this problem, we propose a mixed-integer linear programming (MILP) model. Given that this problem falls into the NP-hard category, an iterative construction-local search-reconstruction algorithm (ICLSRA) is designed. Specifically designed by incorporating construction, local search, and reconstruction processes that have different roles, this algorithm strikes a balance between local and global search. Comparative analysis with the MILP model and state-of-the-art algorithms demonstrates the superiority of ICLSRA in achieving efficient solutions for the DRHHFBSP.
ISSN:2210-6502
DOI:10.1016/j.swevo.2024.101681