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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| Published in: | Swarm and evolutionary computation Vol. 90; p. 101681 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.10.2024
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| ISSN: | 2210-6502 |
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| Abstract | •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. |
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| AbstractList | •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. |
| ArticleNumber | 101681 |
| Author | Zhang, Biao Lu, Chao Zou, Wen-qiang He, Peng Meng, Lei-lei |
| Author_xml | – sequence: 1 givenname: Peng surname: He fullname: He, Peng organization: School of Computer Science, Liaocheng University, Liaocheng, 252000, PR China – sequence: 2 givenname: Biao orcidid: 0000-0003-4148-8172 surname: Zhang fullname: Zhang, Biao email: zhangbiao@lcu-cs.com organization: School of Computer Science, Liaocheng University, Liaocheng, 252000, PR China – sequence: 3 givenname: Chao surname: Lu fullname: Lu, Chao organization: School of Computer Science, China University of Geosciences, Wuhan, 430074, PR China – sequence: 4 givenname: Lei-lei orcidid: 0000-0003-1439-4832 surname: Meng fullname: Meng, Lei-lei organization: School of Computer Science, Liaocheng University, Liaocheng, 252000, PR China – sequence: 5 givenname: Wen-qiang surname: Zou fullname: Zou, Wen-qiang organization: School of Computer Science, Liaocheng University, Liaocheng, 252000, PR China |
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| Keywords | Distributed hybrid flowshop scheduling Batch scheduling Reentrant scheduling Heuristic |
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| SubjectTerms | Batch scheduling Distributed hybrid flowshop scheduling Heuristic Reentrant scheduling |
| Title | Optimizing distributed reentrant heterogeneous hybrid flowshop batch scheduling problem: Iterative construction-local search-reconstruction algorithm |
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