A hybrid genetic algorithm for task allocation in multicomputers
A hybrid genetic algorithm for the task allocation problem (HGATA) in multicomputers is presented. It minimizes the possibility of premature convergence and finds good solutions in a reasonable time. HGATA includes elitist ranking selection, variable rates for the genetic operators, the inversion op...
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| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | conferenceObject |
| منشور في: |
2018
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/7957 http://dx.doi.org/10.13140/RG.2.1.3960.5608 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.researchgate.net/publication/201976071_A_Hybrid_Genetic_Algorithm_for_Task_Allocation_in_Multicomputers |
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إضافة وسم
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| _version_ | 1864513483495702528 |
|---|---|
| author | Mansour, Nashat |
| author_facet | Mansour, Nashat |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat |
| dc.date.none.fl_str_mv | 2018-05-29T13:18:39Z 2018-05-29T13:18:39Z 2018-05-29 |
| dc.identifier.none.fl_str_mv | 1-55860-208-9 http://hdl.handle.net/10725/7957 http://dx.doi.org/10.13140/RG.2.1.3960.5608 Fox, G. C., & Mansour, N. (1991, July). A Hybrid Genetic Algorithm for Task Allocation in Multicomputers. In Proc. of Int. Conf. on Genetic Algorithms. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.researchgate.net/publication/201976071_A_Hybrid_Genetic_Algorithm_for_Task_Allocation_in_Multicomputers |
| dc.language.none.fl_str_mv | en |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | A hybrid genetic algorithm for task allocation in multicomputers |
| dc.type.none.fl_str_mv | Conference Paper / Proceeding info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/conferenceObject |
| description | A hybrid genetic algorithm for the task allocation problem (HGATA) in multicomputers is presented. It minimizes the possibility of premature convergence and finds good solutions in a reasonable time. HGATA includes elitist ranking selection, variable rates for the genetic operators, the inversion operator and hill-climbing of individuals. Hill-climbing is done by a simple heuristic procedure tailored to the task allocation problem. HGATA also makes use of problem-specific information to evade some computational costs and to reinforce favorable aspects of the genetic search at some appropriate points. The experimental results on realistic test cases support the HGATA approach for task allocation. |
| eu_rights_str_mv | openAccess |
| format | conferenceObject |
| id | LAURepo_f6bc8cdab92011e373c58fd40b910934 |
| identifier_str_mv | 1-55860-208-9 Fox, G. C., & Mansour, N. (1991, July). A Hybrid Genetic Algorithm for Task Allocation in Multicomputers. In Proc. of Int. Conf. on Genetic Algorithms. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/7957 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A hybrid genetic algorithm for task allocation in multicomputersMansour, NashatA hybrid genetic algorithm for the task allocation problem (HGATA) in multicomputers is presented. It minimizes the possibility of premature convergence and finds good solutions in a reasonable time. HGATA includes elitist ranking selection, variable rates for the genetic operators, the inversion operator and hill-climbing of individuals. Hill-climbing is done by a simple heuristic procedure tailored to the task allocation problem. HGATA also makes use of problem-specific information to evade some computational costs and to reinforce favorable aspects of the genetic search at some appropriate points. The experimental results on realistic test cases support the HGATA approach for task allocation.N/A2018-05-29T13:18:39Z2018-05-29T13:18:39Z2018-05-29Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1-55860-208-9http://hdl.handle.net/10725/7957http://dx.doi.org/10.13140/RG.2.1.3960.5608Fox, G. C., & Mansour, N. (1991, July). A Hybrid Genetic Algorithm for Task Allocation in Multicomputers. In Proc. of Int. Conf. on Genetic Algorithms.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://www.researchgate.net/publication/201976071_A_Hybrid_Genetic_Algorithm_for_Task_Allocation_in_Multicomputerseninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/79572021-03-19T10:43:16Z |
| spellingShingle | A hybrid genetic algorithm for task allocation in multicomputers Mansour, Nashat |
| status_str | publishedVersion |
| title | A hybrid genetic algorithm for task allocation in multicomputers |
| title_full | A hybrid genetic algorithm for task allocation in multicomputers |
| title_fullStr | A hybrid genetic algorithm for task allocation in multicomputers |
| title_full_unstemmed | A hybrid genetic algorithm for task allocation in multicomputers |
| title_short | A hybrid genetic algorithm for task allocation in multicomputers |
| title_sort | A hybrid genetic algorithm for task allocation in multicomputers |
| url | http://hdl.handle.net/10725/7957 http://dx.doi.org/10.13140/RG.2.1.3960.5608 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.researchgate.net/publication/201976071_A_Hybrid_Genetic_Algorithm_for_Task_Allocation_in_Multicomputers |