Application of an evolutionary algorithm-based ensemble model to job-shop scheduling
In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-s...
| Main Authors: | , , , , , , , |
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| Format: | Article |
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Springer Verlag
2019
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| _version_ | 1825722038123233280 |
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| author | Tan, Choo Jun Neoh, Siew Chin Lim, Chee Peng Hanoun, Samer Wong, Wai Peng Loo, Chu Kiong Zhang, Li Nahavandi, Saeid |
| author_facet | Tan, Choo Jun Neoh, Siew Chin Lim, Chee Peng Hanoun, Samer Wong, Wai Peng Loo, Chu Kiong Zhang, Li Nahavandi, Saeid |
| author_sort | Tan, Choo Jun |
| collection | UM |
| description | In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems. © 2017, Springer Science+Business Media New York. |
| first_indexed | 2024-03-06T05:59:32Z |
| format | Article |
| id | um.eprints-23319 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:59:32Z |
| publishDate | 2019 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | um.eprints-233192020-01-06T03:20:47Z http://eprints.um.edu.my/23319/ Application of an evolutionary algorithm-based ensemble model to job-shop scheduling Tan, Choo Jun Neoh, Siew Chin Lim, Chee Peng Hanoun, Samer Wong, Wai Peng Loo, Chu Kiong Zhang, Li Nahavandi, Saeid QA75 Electronic computers. Computer science In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems. © 2017, Springer Science+Business Media New York. Springer Verlag 2019 Article PeerReviewed Tan, Choo Jun and Neoh, Siew Chin and Lim, Chee Peng and Hanoun, Samer and Wong, Wai Peng and Loo, Chu Kiong and Zhang, Li and Nahavandi, Saeid (2019) Application of an evolutionary algorithm-based ensemble model to job-shop scheduling. Journal of Intelligent Manufacturing, 30 (2). pp. 879-890. ISSN 0956-5515, DOI https://doi.org/10.1007/s10845-016-1291-1 <https://doi.org/10.1007/s10845-016-1291-1>. https://doi.org/10.1007/s10845-016-1291-1 doi:10.1007/s10845-016-1291-1 |
| spellingShingle | QA75 Electronic computers. Computer science Tan, Choo Jun Neoh, Siew Chin Lim, Chee Peng Hanoun, Samer Wong, Wai Peng Loo, Chu Kiong Zhang, Li Nahavandi, Saeid Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title | Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title_full | Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title_fullStr | Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title_full_unstemmed | Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title_short | Application of an evolutionary algorithm-based ensemble model to job-shop scheduling |
| title_sort | application of an evolutionary algorithm based ensemble model to job shop scheduling |
| topic | QA75 Electronic computers. Computer science |
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