Dynamic distributed flexible job-shop scheduling problem considering operation inspection
The classical distributed flexible job-shop scheduling problem (DFJSP) only considers static manufacturing environment and ignores operation inspection. However, in the real production, the manufacturing environment is normally dynamic and the operation inspection is very important to prevent unqual...
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| Published in | Expert systems with applications Vol. 224; p. 119840 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
15.08.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4174 1873-6793 |
| DOI | 10.1016/j.eswa.2023.119840 |
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| Abstract | The classical distributed flexible job-shop scheduling problem (DFJSP) only considers static manufacturing environment and ignores operation inspection. However, in the real production, the manufacturing environment is normally dynamic and the operation inspection is very important to prevent unqualified products from being transported to the next manufacturing stage. In this paper, we first propose a dynamic distributed flexible job-shop scheduling problem considering operation inspection (DFJSPI). A modified memetic algorithm (MMA) is then designed to solve the DFJSPI aiming at to minimize the makespan and total energy consumption. In the MMA, a novel five-layer encoding method and an initialization method are developed to generate a high-quality initial population. A hybrid rescheduling method including three rescheduling strategies is developed to handle different inspection results. Some effective crossover operators, mutation operators and a local search operator are designed to expand the solution space of MMA and to accelerate its convergence speed. A total of 100 DFJSPI benchmark instances are constructed to test the performance of the MMA. Extensive experiments carried out to compare the proposed MMA with other three well-known algorithms demonstrate that the MMA has obvious superiority in almost all tested instances. This study will be beneficial for the production managers to deal with dynamical distributed manufacturing with operation inspection, especially providing reference for the manufacturing systems with operation reworking and scrapping. |
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| AbstractList | The classical distributed flexible job-shop scheduling problem (DFJSP) only considers static manufacturing environment and ignores operation inspection. However, in the real production, the manufacturing environment is normally dynamic and the operation inspection is very important to prevent unqualified products from being transported to the next manufacturing stage. In this paper, we first propose a dynamic distributed flexible job-shop scheduling problem considering operation inspection (DFJSPI). A modified memetic algorithm (MMA) is then designed to solve the DFJSPI aiming at to minimize the makespan and total energy consumption. In the MMA, a novel five-layer encoding method and an initialization method are developed to generate a high-quality initial population. A hybrid rescheduling method including three rescheduling strategies is developed to handle different inspection results. Some effective crossover operators, mutation operators and a local search operator are designed to expand the solution space of MMA and to accelerate its convergence speed. A total of 100 DFJSPI benchmark instances are constructed to test the performance of the MMA. Extensive experiments carried out to compare the proposed MMA with other three well-known algorithms demonstrate that the MMA has obvious superiority in almost all tested instances. This study will be beneficial for the production managers to deal with dynamical distributed manufacturing with operation inspection, especially providing reference for the manufacturing systems with operation reworking and scrapping. |
| ArticleNumber | 119840 |
| Author | Gong, Guiliang Luo, Qiang Li, Xiaoqiang Zhang, Liqiang Zhu, Kaikai Huang, Dan Peng, Ningtao |
| Author_xml | – sequence: 1 givenname: Kaikai orcidid: 0000-0001-5693-4783 surname: Zhu fullname: Zhu, Kaikai organization: Department of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China – sequence: 2 givenname: Guiliang orcidid: 0000-0002-3063-0770 surname: Gong fullname: Gong, Guiliang email: guiliang_gong@163.com organization: Department of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China – sequence: 3 givenname: Ningtao surname: Peng fullname: Peng, Ningtao organization: Department of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China – sequence: 4 givenname: Liqiang surname: Zhang fullname: Zhang, Liqiang organization: Department of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China – sequence: 5 givenname: Dan surname: Huang fullname: Huang, Dan organization: Department of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China – sequence: 6 givenname: Qiang surname: Luo fullname: Luo, Qiang organization: State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China – sequence: 7 givenname: Xiaoqiang surname: Li fullname: Li, Xiaoqiang organization: Department of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China |
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| Keywords | Memetic algorithm Dynamic distributed flexible job-shop scheduling Multi-objective optimization Operation inspection |
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| SubjectTerms | Dynamic distributed flexible job-shop scheduling Memetic algorithm Multi-objective optimization Operation inspection |
| Title | Dynamic distributed flexible job-shop scheduling problem considering operation inspection |
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