{"title":"序列分布置换流水车间调度问题的合作迭代贪心算法","authors":"Biao Han, Quan-Ke Pan, Liang Gao","doi":"10.1080/00207543.2023.2255681","DOIUrl":null,"url":null,"abstract":"AbstractThis paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process that contains two production stages linked by a transportation stage, where the scheduling problem in each production stage can be seen as a distributed permutation flowshop scheduling problem (DPFSP). A sequence-based mixed-integer linear programming model is established. A solution representation consisting of two components, one component per stage, is presented and a makespan calculation method is given for the representation. Two suites of accelerations based on the insertion neighbourhood are proposed to reduce the computational complexity. A cooperative iterated greedy (CIG) algorithm is developed with two subloops, each of which optimises a component of the solution. A collaboration mechanism is used to conduct the collaboration of the two subloops effectively. Problem-specific operators including the NEH-based heuristics, destruction, reconstruction and three local search procedures, are designed. Extensive computational experiments and statistical analysis verify the validity of the model, the effectiveness of the proposed CIG algorithm and the superiority of the proposed CIG over the existing methods for solving the problem under consideration.KEYWORDS: Distributed schedulingiterated greedymakespanpermutation flowshopaccelerations Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Additional informationFundingThis research is partially supported by the National Science Foundation of China 62273221 and 61973203, and Program of Shanghai Academic/Technology Research Leader 21XD1401000.Notes on contributorsBiao HanBiao Han received the BS degree from Shanghai Ocean University, Shanghai, China, in 2020. He is currently working toward the MA degree at Shanghai University, China. His research focuses on algorithm design of distributed flowshop scheduling.Quan-Ke PanQuan-ke Pan received the BSc degree and the PhD degree from Nanjing university of Aeronautics and Astronautics, Nanjing, China, in 1993 and 2003, respectively. From 2003 to 2011, he was with School of Computer Science Department, Liaocheng University, where he became a Full Professor in 2006. From 2011 to 2014, he was with State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang, China. From 2014 to 2015, he was with State Key Laboratory of Digital Manufacturing and Equipment Technology (Huazhong University of Science & Technology). He has been with School of Mechatronic Engineering and Automation, Shanghai University since 2015. His current research interests include intelligent optimisation and scheduling algorithms.Liang GaoLiang Gao received the BSc degree in mechatronic engineering from Xidian University, Xi’an, China, in 1996, and the PhD degree in mechatronic engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is a Professor of the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and Director of National Center of Technology Innovation for Intelligent Design and Numerical Control. His current research interests include optimisation in design and manufacturing.","PeriodicalId":14307,"journal":{"name":"International Journal of Production Research","volume":"42 1","pages":"0"},"PeriodicalIF":7.0000,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A cooperative iterated greedy algorithm for the serial distributed permutation flowshop scheduling problem\",\"authors\":\"Biao Han, Quan-Ke Pan, Liang Gao\",\"doi\":\"10.1080/00207543.2023.2255681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractThis paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process that contains two production stages linked by a transportation stage, where the scheduling problem in each production stage can be seen as a distributed permutation flowshop scheduling problem (DPFSP). A sequence-based mixed-integer linear programming model is established. A solution representation consisting of two components, one component per stage, is presented and a makespan calculation method is given for the representation. Two suites of accelerations based on the insertion neighbourhood are proposed to reduce the computational complexity. A cooperative iterated greedy (CIG) algorithm is developed with two subloops, each of which optimises a component of the solution. A collaboration mechanism is used to conduct the collaboration of the two subloops effectively. Problem-specific operators including the NEH-based heuristics, destruction, reconstruction and three local search procedures, are designed. Extensive computational experiments and statistical analysis verify the validity of the model, the effectiveness of the proposed CIG algorithm and the superiority of the proposed CIG over the existing methods for solving the problem under consideration.KEYWORDS: Distributed schedulingiterated greedymakespanpermutation flowshopaccelerations Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Additional informationFundingThis research is partially supported by the National Science Foundation of China 62273221 and 61973203, and Program of Shanghai Academic/Technology Research Leader 21XD1401000.Notes on contributorsBiao HanBiao Han received the BS degree from Shanghai Ocean University, Shanghai, China, in 2020. He is currently working toward the MA degree at Shanghai University, China. His research focuses on algorithm design of distributed flowshop scheduling.Quan-Ke PanQuan-ke Pan received the BSc degree and the PhD degree from Nanjing university of Aeronautics and Astronautics, Nanjing, China, in 1993 and 2003, respectively. From 2003 to 2011, he was with School of Computer Science Department, Liaocheng University, where he became a Full Professor in 2006. From 2011 to 2014, he was with State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang, China. From 2014 to 2015, he was with State Key Laboratory of Digital Manufacturing and Equipment Technology (Huazhong University of Science & Technology). He has been with School of Mechatronic Engineering and Automation, Shanghai University since 2015. His current research interests include intelligent optimisation and scheduling algorithms.Liang GaoLiang Gao received the BSc degree in mechatronic engineering from Xidian University, Xi’an, China, in 1996, and the PhD degree in mechatronic engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is a Professor of the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and Director of National Center of Technology Innovation for Intelligent Design and Numerical Control. His current research interests include optimisation in design and manufacturing.\",\"PeriodicalId\":14307,\"journal\":{\"name\":\"International Journal of Production Research\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2023-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Production Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/00207543.2023.2255681\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Production Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00207543.2023.2255681","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
A cooperative iterated greedy algorithm for the serial distributed permutation flowshop scheduling problem
AbstractThis paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process that contains two production stages linked by a transportation stage, where the scheduling problem in each production stage can be seen as a distributed permutation flowshop scheduling problem (DPFSP). A sequence-based mixed-integer linear programming model is established. A solution representation consisting of two components, one component per stage, is presented and a makespan calculation method is given for the representation. Two suites of accelerations based on the insertion neighbourhood are proposed to reduce the computational complexity. A cooperative iterated greedy (CIG) algorithm is developed with two subloops, each of which optimises a component of the solution. A collaboration mechanism is used to conduct the collaboration of the two subloops effectively. Problem-specific operators including the NEH-based heuristics, destruction, reconstruction and three local search procedures, are designed. Extensive computational experiments and statistical analysis verify the validity of the model, the effectiveness of the proposed CIG algorithm and the superiority of the proposed CIG over the existing methods for solving the problem under consideration.KEYWORDS: Distributed schedulingiterated greedymakespanpermutation flowshopaccelerations Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Additional informationFundingThis research is partially supported by the National Science Foundation of China 62273221 and 61973203, and Program of Shanghai Academic/Technology Research Leader 21XD1401000.Notes on contributorsBiao HanBiao Han received the BS degree from Shanghai Ocean University, Shanghai, China, in 2020. He is currently working toward the MA degree at Shanghai University, China. His research focuses on algorithm design of distributed flowshop scheduling.Quan-Ke PanQuan-ke Pan received the BSc degree and the PhD degree from Nanjing university of Aeronautics and Astronautics, Nanjing, China, in 1993 and 2003, respectively. From 2003 to 2011, he was with School of Computer Science Department, Liaocheng University, where he became a Full Professor in 2006. From 2011 to 2014, he was with State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University), Shenyang, China. From 2014 to 2015, he was with State Key Laboratory of Digital Manufacturing and Equipment Technology (Huazhong University of Science & Technology). He has been with School of Mechatronic Engineering and Automation, Shanghai University since 2015. His current research interests include intelligent optimisation and scheduling algorithms.Liang GaoLiang Gao received the BSc degree in mechatronic engineering from Xidian University, Xi’an, China, in 1996, and the PhD degree in mechatronic engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2002. He is a Professor of the Department of Industrial and Manufacturing System Engineering, School of Mechanical Science and Engineering, HUST and Director of National Center of Technology Innovation for Intelligent Design and Numerical Control. His current research interests include optimisation in design and manufacturing.
期刊介绍:
The International Journal of Production Research (IJPR), published since 1961, is a well-established, highly successful and leading journal reporting manufacturing, production and operations management research.
IJPR is published 24 times a year and includes papers on innovation management, design of products, manufacturing processes, production and logistics systems. Production economics, the essential behaviour of production resources and systems as well as the complex decision problems that arise in design, management and control of production and logistics systems are considered.
IJPR is a journal for researchers and professors in mechanical engineering, industrial and systems engineering, operations research and management science, and business. It is also an informative reference for industrial managers looking to improve the efficiency and effectiveness of their production systems.