Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
As regards distributed hybrid flow shop scheduling with sequence-dependent setup times (DHFSP-SDST), three novel mixed-integer linear programming (MILP) models and a constraint programming (CP) model are formulated for the same-factory and different-factory environments. The three novel MILP models...
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| Veröffentlicht in: | Swarm and evolutionary computation Jg. 71; S. 101058 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.06.2022
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| ISSN: | 2210-6502 |
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| Abstract | As regards distributed hybrid flow shop scheduling with sequence-dependent setup times (DHFSP-SDST), three novel mixed-integer linear programming (MILP) models and a constraint programming (CP) model are formulated for the same-factory and different-factory environments. The three novel MILP models are based on two different modeling ideas. The existing MILP model and the three proposed MILP models are compared in detail from several aspects, such as binary decision variables, continuous decision variables, constraints, solution performance and solution time. By solving the benchmarks in existing studies, the effectiveness and superiority of the proposed MILP and CP models are proved. Experimental results show that the MILP model of sequence-based modeling idea performs best, the MILP model of adjacent sequence-based modeling idea takes the second place and the existing MILP model of position-based modeling idea performs worst. The CP model is more efficient and effective than MILP models. In addition, compared with the existing meta-heuristic algorithms (e.g., DABC and IABC), the proposed MILP models prove the optimal solutions of 37 instances and improve 17 current best solutions. The CP model solves all the 45 instances to optimality and improves 19 current best solutions for benchmarks in the existing studies |
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| AbstractList | As regards distributed hybrid flow shop scheduling with sequence-dependent setup times (DHFSP-SDST), three novel mixed-integer linear programming (MILP) models and a constraint programming (CP) model are formulated for the same-factory and different-factory environments. The three novel MILP models are based on two different modeling ideas. The existing MILP model and the three proposed MILP models are compared in detail from several aspects, such as binary decision variables, continuous decision variables, constraints, solution performance and solution time. By solving the benchmarks in existing studies, the effectiveness and superiority of the proposed MILP and CP models are proved. Experimental results show that the MILP model of sequence-based modeling idea performs best, the MILP model of adjacent sequence-based modeling idea takes the second place and the existing MILP model of position-based modeling idea performs worst. The CP model is more efficient and effective than MILP models. In addition, compared with the existing meta-heuristic algorithms (e.g., DABC and IABC), the proposed MILP models prove the optimal solutions of 37 instances and improve 17 current best solutions. The CP model solves all the 45 instances to optimality and improves 19 current best solutions for benchmarks in the existing studies |
| ArticleNumber | 101058 |
| Author | Zhang, Biao Chaoyong, Zhang Ren, Yaping Meng, Leilei Gao, Kaizhou Sang, Hongyan |
| Author_xml | – sequence: 1 givenname: Leilei orcidid: 0000-0003-1439-4832 surname: Meng fullname: Meng, Leilei organization: School of Computer Science, Liaocheng University, Liaocheng 252000, China – sequence: 2 givenname: Kaizhou surname: Gao fullname: Gao, Kaizhou email: gaokaizh@aliyun.com organization: School of Computer Science, Liaocheng University, Liaocheng 252000, China – sequence: 3 givenname: Yaping surname: Ren fullname: Ren, Yaping organization: Department of Industrial Engineering, School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China – sequence: 4 givenname: Biao surname: Zhang fullname: Zhang, Biao organization: School of Computer Science, Liaocheng University, Liaocheng 252000, China – sequence: 5 givenname: Hongyan surname: Sang fullname: Sang, Hongyan organization: School of Computer Science, Liaocheng University, Liaocheng 252000, China – sequence: 6 givenname: Zhang surname: Chaoyong fullname: Chaoyong, Zhang organization: State Key Lab of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China |
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| Keywords | Modeling idea Setup time Constraint programming Mixed-integer linear programming Distributed hybrid flow shop scheduling |
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