A tri-individual iterated greedy algorithm for the distributed hybrid flow shop with blocking

Scheduling problem with blocking is an attractive research direction due to its wide practical applications. However, in the distributed hybrid flow shop problem (DHFSP), there are few studies on blocking constraints. In this article, we study a distributed hybrid flow shop scheduling problem with b...

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Veröffentlicht in:Expert systems with applications Jg. 237; S. 121667
Hauptverfasser: Liu, Feige, Li, Guiling, Lu, Chao, Yin, Lvjiang, Zhou, Jiajun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.03.2024
Schlagworte:
Active decoding
Blocking
Distributed hybrid flow shop scheduling problems
Diversified iterated greedy algorithm
Heuristics
Problem-specific knowledge
Blocking
Diversified iterated greedy algorithm
Problem-specific knowledge
Active decoding
Heuristics
Distributed hybrid flow shop scheduling problems
ISSN:0957-4174, 1873-6793
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Zusammenfassung:Scheduling problem with blocking is an attractive research direction due to its wide practical applications. However, in the distributed hybrid flow shop problem (DHFSP), there are few studies on blocking constraints. In this article, we study a distributed hybrid flow shop scheduling problem with blocking constraints (DBHFSP), where the goal is to minimize the maximum completion time, and propose a tri-individual iterated greedy (TIG) algorithm based on the characteristics of the DBHFSP. First, an active decoding strategy is designed to reduce the idle time of machines. Afterward, a framework of multiple iterative solutions is designed to enhance the diversity of the solutions, in which the multiple solutions are generated through a neighborhood search. Then, a heuristic rule based on blocking constraint is proposed to generate promising initial solutions. In addition, an insertion-based search strategy based on rotating critical factories is designed to accelerate the convergence speed of the TIG algorithm. Finally, the proposed algorithm is compared with state-of-the-art algorithms and classical intelligent optimization algorithms. The experimental results show that the TIG algorithm is superior to the comparison algorithm in solving the DBHFSP.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.121667