A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem
Job shop scheduling problem (JSP) is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem (FJSP) is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each pro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://eprints.nottingham.ac.uk/65351/ |
| _version_ | 1848800214664609792 |
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| author | Feng, Yi Liu, Mengru Zhang, Yuqian Wang, Jinglin Selisteanu, Dan |
| author_facet | Feng, Yi Liu, Mengru Zhang, Yuqian Wang, Jinglin Selisteanu, Dan |
| author_sort | Feng, Yi |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Job shop scheduling problem (JSP) is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem (FJSP) is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each process from a given set, which introduces another decision element within the job path, making FJSP be more difficult than traditional JSP. In this paper, a variant of grasshopper optimization algorithm (GOA) named dynamic opposite learning assisted GOA (DOLGOA) is proposed to solve FJSP. )e recently proposed dynamic opposite learning (DOL) strategy adopts the asymmetric search space to improve the exploitation ability of the algorithm and increase the possibility of finding the global optimum. Various popular benchmarks from CEC 2014 and FJSP are used to evaluate the performance of DOLGOA. Numerical results with comparisons of other classic algorithms show that DOLGOA gets obvious improvement for solving global optimization problems and is well-performed when solving FJSP. |
| first_indexed | 2025-11-14T20:48:00Z |
| format | Article |
| id | nottingham-65351 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:48:00Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-653512021-06-04T07:36:37Z https://eprints.nottingham.ac.uk/65351/ A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem Feng, Yi Liu, Mengru Zhang, Yuqian Wang, Jinglin Selisteanu, Dan Job shop scheduling problem (JSP) is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem (FJSP) is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each process from a given set, which introduces another decision element within the job path, making FJSP be more difficult than traditional JSP. In this paper, a variant of grasshopper optimization algorithm (GOA) named dynamic opposite learning assisted GOA (DOLGOA) is proposed to solve FJSP. )e recently proposed dynamic opposite learning (DOL) strategy adopts the asymmetric search space to improve the exploitation ability of the algorithm and increase the possibility of finding the global optimum. Various popular benchmarks from CEC 2014 and FJSP are used to evaluate the performance of DOLGOA. Numerical results with comparisons of other classic algorithms show that DOLGOA gets obvious improvement for solving global optimization problems and is well-performed when solving FJSP. 2020-12-30 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/65351/1/gold%204.pdf Feng, Yi, Liu, Mengru, Zhang, Yuqian, Wang, Jinglin and Selisteanu, Dan (2020) A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem. Complexity, 2020 . pp. 1-19. ISSN 1076-2787 http://dx.doi.org/10.1155/2020/8870783 doi:10.1155/2020/8870783 doi:10.1155/2020/8870783 |
| spellingShingle | Feng, Yi Liu, Mengru Zhang, Yuqian Wang, Jinglin Selisteanu, Dan A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title | A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title_full | A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title_fullStr | A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title_full_unstemmed | A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title_short | A dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| title_sort | dynamic opposite learning assisted grasshopper optimization algorithm for the flexible job scheduling problem |
| url | https://eprints.nottingham.ac.uk/65351/ https://eprints.nottingham.ac.uk/65351/ https://eprints.nottingham.ac.uk/65351/ |