Swarm and Evolutionary Computation
This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| منشور في: |
2022
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| الوصول للمادة أونلاين: | https://dspace.auk.edu.kw/handle/11675/9603 https://www.sciencedirect.com/science/article/abs/pii/S2210650222000979 |
| الوسوم: |
إضافة وسم
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| _version_ | 1870679728464068608 |
|---|---|
| author | El-Abd, Mohammed |
| author2 | Abou Doush, Iyad |
| author2_role | author |
| author_facet | El-Abd, Mohammed Abou Doush, Iyad |
| author_role | author |
| dc.contributor.none.fl_str_mv | Al-Betar, Mohammed Azmi Awadallah, Mohammed Alyasseri, Zaid Abdi Alkareem Makhadmeh, Sharif |
| dc.creator.none.fl_str_mv | El-Abd, Mohammed Abou Doush, Iyad |
| dc.date.none.fl_str_mv | 2022-07-14 2023-04-09T10:32:27Z 2023-04-09T10:32:27Z |
| dc.identifier.none.fl_str_mv | Abu Doush, I., Al-Betar, M. A., Awadallah, M. A., Alyasseri, Z. A. A., Makhadmeh, S. N., & El-Abd, M. (2022). Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking. Swarm and Evolutionary Computation, 74, 101127. https://doi.org/10.1016/j.swevo.2022.101127 https://dspace.auk.edu.kw/handle/11675/9603 https://www.sciencedirect.com/science/article/abs/pii/S2210650222000979 |
| dc.publisher.none.fl_str_mv | Elsevier |
| dc.relation.none.fl_str_mv | College of Engineering & Applied sciences |
| dc.title.none.fl_str_mv | Swarm and Evolutionary Computation |
| dc.type.none.fl_str_mv | Peer Reviewed Journal Article info:eu-repo/semantics/publishedVersion |
| description | This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then the harmony search algorithm iterates to look for and to develop a new solution enhanced by using neighboring heuristics. A migration process is applied, after a predefined number of iterations, to perform an exchange between some individuals in islands. The proposed algorithm is evaluated using 12 real-world datasets, each with 10 instances. A sensitivity analysis of the island model parameters is conducted to choose values that minimize the total flow time. The evaluation is conducted using two criteria, the number of evolutions and the Central Processing Unit (CPU) time using six comparative methods and sixteen comparative methods, respectively. For the first criterion, the proposed algorithm excels other comparative algorithms when solving instances of four datasets. For the second criterion, the proposed algorithm outperforms other comparative methods in six out of the twelve datasets. In conclusion, The obtained results prove the efficiency and competitiveness of the proposed algorithm when tackling the blocking flow-shop scheduling problem. |
| id | AUKR_387c8bfd5641fa8a8e9db789dff70155 |
| identifier_str_mv | Abu Doush, I., Al-Betar, M. A., Awadallah, M. A., Alyasseri, Z. A. A., Makhadmeh, S. N., & El-Abd, M. (2022). Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking. Swarm and Evolutionary Computation, 74, 101127. https://doi.org/10.1016/j.swevo.2022.101127 |
| network_acronym_str | AUKR |
| network_name_str | AU Kuwait Rep |
| oai_identifier_str | oai:dspace.auk.edu.kw:11675/9603 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | Elsevier |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Swarm and Evolutionary ComputationEl-Abd, Mohammed Abou Doush, IyadThis paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then the harmony search algorithm iterates to look for and to develop a new solution enhanced by using neighboring heuristics. A migration process is applied, after a predefined number of iterations, to perform an exchange between some individuals in islands. The proposed algorithm is evaluated using 12 real-world datasets, each with 10 instances. A sensitivity analysis of the island model parameters is conducted to choose values that minimize the total flow time. The evaluation is conducted using two criteria, the number of evolutions and the Central Processing Unit (CPU) time using six comparative methods and sixteen comparative methods, respectively. For the first criterion, the proposed algorithm excels other comparative algorithms when solving instances of four datasets. For the second criterion, the proposed algorithm outperforms other comparative methods in six out of the twelve datasets. In conclusion, The obtained results prove the efficiency and competitiveness of the proposed algorithm when tackling the blocking flow-shop scheduling problem.ElsevierAl-Betar, Mohammed Azmi Awadallah, Mohammed Alyasseri, Zaid Abdi AlkareemMakhadmeh, Sharif2023-04-09T10:32:27Z2023-04-09T10:32:27Z2022-07-14Peer ReviewedJournal Articleinfo:eu-repo/semantics/publishedVersionAbu Doush, I., Al-Betar, M. A., Awadallah, M. A., Alyasseri, Z. A. A., Makhadmeh, S. N., & El-Abd, M. (2022). Island neighboring heuristics harmony search algorithm for flow shop scheduling with blocking. Swarm and Evolutionary Computation, 74, 101127. https://doi.org/10.1016/j.swevo.2022.101127https://dspace.auk.edu.kw/handle/11675/9603https://www.sciencedirect.com/science/article/abs/pii/S2210650222000979College of Engineering & Applied sciencesoai:dspace.auk.edu.kw:11675/96032025-06-23T06:33:43Z |
| spellingShingle | Swarm and Evolutionary Computation El-Abd, Mohammed |
| status_str | publishedVersion |
| title | Swarm and Evolutionary Computation |
| title_full | Swarm and Evolutionary Computation |
| title_fullStr | Swarm and Evolutionary Computation |
| title_full_unstemmed | Swarm and Evolutionary Computation |
| title_short | Swarm and Evolutionary Computation |
| title_sort | Swarm and Evolutionary Computation |
| url | https://dspace.auk.edu.kw/handle/11675/9603 https://www.sciencedirect.com/science/article/abs/pii/S2210650222000979 |