Self-Adaptive Population-Based Iterated Greedy Algorithm for Distributed Permutation Flowshop Scheduling Problem with Part of Jobs Subject to a Common Deadline Constraint
Although the distributed permutation flowshop scheduling problem (DPFSP) has recently received extensive research attention, most studies assume that either all jobs have due date constraints or none of them do. Nevertheless, in practice, it is very common to schedule jobs with due dates alongside j...
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| Vydané v: | Expert systems with applications Ročník 248; s. 123278 |
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| Hlavní autori: | , , , , , |
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| Jazyk: | English |
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Elsevier Ltd
15.08.2024
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | Although the distributed permutation flowshop scheduling problem (DPFSP) has recently received extensive research attention, most studies assume that either all jobs have due date constraints or none of them do. Nevertheless, in practice, it is very common to schedule jobs with due dates alongside jobs without a due date. This paper addresses a DPFSP with part of jobs subject to a common deadline (DPFSP-PJCD). The objective is to minimize the total completion time. We establish a mathematical model and propose a Self-adaptive Population-based Iterated Greedy (SPIG) algorithm that is specifically tailored to the characteristics of the problem. We design a hybrid constructive heuristic to generate a population of potentially high-quality solutions. We introduce an insertion-based acceleration method that combines three distinct accelerations to improve operational efficiency. We propose some effective operators to carry out the selection, destruction, and construction of solutions, as well as a local search mechanism, to balance the exploitation and exploration of the algorithm. Additionally, we employ a self-adaptive method to determine a key algorithmic parameter depending on the search phase and search space. We also utilize a self-adjustment insertion procedure to handle infeasible solutions. Through comprehensive experimental evaluations, we demonstrate that the proposed SPIG outperforms five state-of-the-art metaheuristics from the closely related literature, providing effective solutions for the DPFSP-PJCD considered. |
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| AbstractList | Although the distributed permutation flowshop scheduling problem (DPFSP) has recently received extensive research attention, most studies assume that either all jobs have due date constraints or none of them do. Nevertheless, in practice, it is very common to schedule jobs with due dates alongside jobs without a due date. This paper addresses a DPFSP with part of jobs subject to a common deadline (DPFSP-PJCD). The objective is to minimize the total completion time. We establish a mathematical model and propose a Self-adaptive Population-based Iterated Greedy (SPIG) algorithm that is specifically tailored to the characteristics of the problem. We design a hybrid constructive heuristic to generate a population of potentially high-quality solutions. We introduce an insertion-based acceleration method that combines three distinct accelerations to improve operational efficiency. We propose some effective operators to carry out the selection, destruction, and construction of solutions, as well as a local search mechanism, to balance the exploitation and exploration of the algorithm. Additionally, we employ a self-adaptive method to determine a key algorithmic parameter depending on the search phase and search space. We also utilize a self-adjustment insertion procedure to handle infeasible solutions. Through comprehensive experimental evaluations, we demonstrate that the proposed SPIG outperforms five state-of-the-art metaheuristics from the closely related literature, providing effective solutions for the DPFSP-PJCD considered. |
| ArticleNumber | 123278 |
| Author | Pan, Quan-Ke Jing, Xue-Lei Li, Qiu-Ying Li, Wei-Min Sang, Hong-Yan Framiñán, Jose M. |
| Author_xml | – sequence: 1 givenname: Qiu-Ying surname: Li fullname: Li, Qiu-Ying email: liqiuying@shu.edu.cn organization: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, PR China – sequence: 2 givenname: Quan-Ke orcidid: 0000-0002-5022-7946 surname: Pan fullname: Pan, Quan-Ke email: panquanke@shu.edu.cn organization: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, PR China – sequence: 3 givenname: Hong-Yan surname: Sang fullname: Sang, Hong-Yan email: sanghongyan@lcu-cs.com organization: School of Computer Science and Technology, Liaocheng University, Liaocheng 252000, PR China – sequence: 4 givenname: Xue-Lei orcidid: 0000-0002-6181-6551 surname: Jing fullname: Jing, Xue-Lei email: jingxuelei@lcu.edu.cn organization: Network Information Center, Liaocheng University, Liaocheng 252000, PR China – sequence: 5 givenname: Jose M. surname: Framiñán fullname: Framiñán, Jose M. email: framinan@us.es organization: Industrial Management, School of Engineering, University of Seville. Camino de los Descubrimientos s/n, 41092 Seville, Spain – sequence: 6 givenname: Wei-Min surname: Li fullname: Li, Wei-Min email: wmli@shu.edu.cn organization: School of Computer Engineering and Science, Shanghai University, Shanghai 200000, PR China |
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| Keywords | Distributed permutation flowshop Scheduling Iterated greedy Total completion time Deadline |
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