Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling
This paper proposes a Pareto-based grouping discrete harmony search algorithm (PGDHS) to solve the multi-objective flexible job shop scheduling problem (FJSP). Two objectives, namely the maximum completion time (makespan) and the mean of earliness and tardiness, are considered simultaneously. Firstl...
| Հիմնական հեղինակներ: | , , , , , |
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| Այլ հեղինակներ: | |
| Ձևաչափ: | Journal Article |
| Լեզու: | English |
| Հրապարակվել է: |
2016
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| Առցանց հասանելիություն: | https://hdl.handle.net/10356/82059 http://hdl.handle.net/10220/39758 |
| _version_ | 1826110943790104576 |
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| author | Gao, Kai Zhou Suganthan, P. N. Pan, Q. K. Chua, Tay Jin Cai, T. J. Chong, C. S. |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Gao, Kai Zhou Suganthan, P. N. Pan, Q. K. Chua, Tay Jin Cai, T. J. Chong, C. S. |
| author_sort | Gao, Kai Zhou |
| collection | NTU |
| description | This paper proposes a Pareto-based grouping discrete harmony search algorithm (PGDHS) to solve the multi-objective flexible job shop scheduling problem (FJSP). Two objectives, namely the maximum completion time (makespan) and the mean of earliness and tardiness, are considered simultaneously. Firstly, two novel heuristics and several existing heuristics are employed to initialize the harmony memory. Secondly, multiple harmony generation strategies are proposed to improve the performance of harmony search algorithm. The operation sequence in a new harmony is produced based on the encoding method and the characteristics of FJSP. Thirdly, two local search methods based on critical path and due date are embedded to enhance the exploitation capability. Finally, extensive computational experiments are carried out using well-known benchmark instances. Three widely used performance measures, number of non-dominated solutions, diversification metric and quality metric, are employed to test the performance of PGDHS algorithm. Computational results and comparisons show the efficiency and effectiveness of the proposed PGDHS algorithm for solving multi-objective flexible job-shop scheduling problem. |
| first_indexed | 2024-10-01T02:42:28Z |
| format | Journal Article |
| id | ntu-10356/82059 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:42:28Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/820592020-09-26T22:09:59Z Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling Gao, Kai Zhou Suganthan, P. N. Pan, Q. K. Chua, Tay Jin Cai, T. J. Chong, C. S. School of Electrical and Electronic Engineering A*STAR SIMTech Flexible job shop scheduling; Harmony search algorithm; Multi-objective optimization; Local search This paper proposes a Pareto-based grouping discrete harmony search algorithm (PGDHS) to solve the multi-objective flexible job shop scheduling problem (FJSP). Two objectives, namely the maximum completion time (makespan) and the mean of earliness and tardiness, are considered simultaneously. Firstly, two novel heuristics and several existing heuristics are employed to initialize the harmony memory. Secondly, multiple harmony generation strategies are proposed to improve the performance of harmony search algorithm. The operation sequence in a new harmony is produced based on the encoding method and the characteristics of FJSP. Thirdly, two local search methods based on critical path and due date are embedded to enhance the exploitation capability. Finally, extensive computational experiments are carried out using well-known benchmark instances. Three widely used performance measures, number of non-dominated solutions, diversification metric and quality metric, are employed to test the performance of PGDHS algorithm. Computational results and comparisons show the efficiency and effectiveness of the proposed PGDHS algorithm for solving multi-objective flexible job-shop scheduling problem. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2016-01-22T07:47:16Z 2019-12-06T14:45:40Z 2016-01-22T07:47:16Z 2019-12-06T14:45:40Z 2014 Journal Article Gao, K., Suganthan, P. N., Pan, Q. K., Chua, T. J., Cai, T. X., & Chong, C. S. (2014). Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling. Information Sciences, 289, 76-90. 0020-0255 https://hdl.handle.net/10356/82059 http://hdl.handle.net/10220/39758 10.1016/j.ins.2014.07.039 en Information Sciences © 2014 Elsevier. This is the author created version of a work that has been peer reviewed and accepted for publication by Information Sciences, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.ins.2014.07.039]. 18 p. application/pdf |
| spellingShingle | Flexible job shop scheduling; Harmony search algorithm; Multi-objective optimization; Local search Gao, Kai Zhou Suganthan, P. N. Pan, Q. K. Chua, Tay Jin Cai, T. J. Chong, C. S. Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title | Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title_full | Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title_fullStr | Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title_full_unstemmed | Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title_short | Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling |
| title_sort | pareto based grouping discrete harmony search algorithm for multi objective flexible job shop scheduling |
| topic | Flexible job shop scheduling; Harmony search algorithm; Multi-objective optimization; Local search |
| url | https://hdl.handle.net/10356/82059 http://hdl.handle.net/10220/39758 |
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