Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem
This study proposes a novel methodology towards using ant colony optimization (ACO) with stochastic demand. In particular, an optimization-simulation-optimization approach is used to solve the Stochastic uncapacitated location-allocation problem with an unknown number of facilities, and an objective...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
2016
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/4981 http://dx.doi.org/10.3934/jimo.2016.12.1215 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=12136 |
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| _version_ | 1864513464960024576 |
|---|---|
| author | El Khoury, John |
| author2 | Arnaout, Jean-Paul Arnaout, Georges |
| author2_role | author author |
| author_facet | El Khoury, John Arnaout, Jean-Paul Arnaout, Georges |
| author_role | author |
| dc.creator.none.fl_str_mv | El Khoury, John Arnaout, Jean-Paul Arnaout, Georges |
| dc.date.none.fl_str_mv | 2016 2017-01-05T11:06:19Z 2017-01-05T11:06:19Z 2017-01-05 |
| dc.identifier.none.fl_str_mv | 1553-166X http://hdl.handle.net/10725/4981 http://dx.doi.org/10.3934/jimo.2016.12.1215 Arnaout, J- P., Arnaout, G., & El Khoury, J. (2016). Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem. Journal of Industrial and Management Optimization, 12(4), 1215 - 1225 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=12136 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Journal of Industrial and Management Optimization (JIMO) |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This study proposes a novel methodology towards using ant colony optimization (ACO) with stochastic demand. In particular, an optimization-simulation-optimization approach is used to solve the Stochastic uncapacitated location-allocation problem with an unknown number of facilities, and an objective of minimizing the fixed and transportation costs. ACO is modeled using discrete event simulation to capture the randomness of customers' demand, and its objective is to optimize the costs. On the other hand, the simulated ACO's parameters are also optimized to guarantee superior solutions. This approach's performance is evaluated by comparing its solutions to the ones obtained using deterministic data. The results show that simulation was able to identify better facility allocations where the deterministic solutions would have been inadequate due to the real randomness of customers' demands. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_432d7e5a6cbbb8bd7674436f2d001a0d |
| identifier_str_mv | 1553-166X Arnaout, J- P., Arnaout, G., & El Khoury, J. (2016). Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem. Journal of Industrial and Management Optimization, 12(4), 1215 - 1225 |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/4981 |
| publishDate | 2016 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problemEl Khoury, JohnArnaout, Jean-PaulArnaout, GeorgesThis study proposes a novel methodology towards using ant colony optimization (ACO) with stochastic demand. In particular, an optimization-simulation-optimization approach is used to solve the Stochastic uncapacitated location-allocation problem with an unknown number of facilities, and an objective of minimizing the fixed and transportation costs. ACO is modeled using discrete event simulation to capture the randomness of customers' demand, and its objective is to optimize the costs. On the other hand, the simulated ACO's parameters are also optimized to guarantee superior solutions. This approach's performance is evaluated by comparing its solutions to the ones obtained using deterministic data. The results show that simulation was able to identify better facility allocations where the deterministic solutions would have been inadequate due to the real randomness of customers' demands.PublishedN/A2017-01-05T11:06:19Z2017-01-05T11:06:19Z20162017-01-05Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1553-166Xhttp://hdl.handle.net/10725/4981http://dx.doi.org/10.3934/jimo.2016.12.1215Arnaout, J- P., Arnaout, G., & El Khoury, J. (2016). Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem. Journal of Industrial and Management Optimization, 12(4), 1215 - 1225http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=12136enJournal of Industrial and Management Optimization (JIMO)info:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/49812021-03-19T10:03:18Z |
| spellingShingle | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem El Khoury, John |
| status_str | publishedVersion |
| title | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| title_full | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| title_fullStr | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| title_full_unstemmed | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| title_short | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| title_sort | Simulation and optimization of ant colony optimization algorithm for the stochastic uncapacitated location-allocation problem |
| url | http://hdl.handle.net/10725/4981 http://dx.doi.org/10.3934/jimo.2016.12.1215 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=12136 |