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Optimization of flow shop scheduling through a hybrid genetic algorithm for manufacturing companies
dc.contributor.author | amelec, viloria | spa |
dc.contributor.author | Martínez Sierra, David | spa |
dc.contributor.author | Duran, Sonia Ethel | spa |
dc.contributor.author | Pallares Rambal, Etelberto | spa |
dc.contributor.author | Hernández-Palma, Hugo | spa |
dc.contributor.author | Martínez Ventura, Jairo Luis | spa |
dc.contributor.author | RONCALLO PICHON, ALBERTO DE JESUS | spa |
dc.contributor.author | Jinete Torres, Leidy José | spa |
dc.date.accessioned | 2020-01-30T13:33:39Z | |
dc.date.available | 2020-01-30T13:33:39Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://hdl.handle.net/11323/5943 | spa |
dc.description.abstract | A task scheduling problem is a process of assigning tasks to a limited set of resources available in a time interval, where certain criteria are optimized. In this way, the sequencing of tasks is directly associated with the executability and optimality of a preset plan and can be found in a wide range of applications, such as: programming flight dispatch at airports, programming production lines in a factory, programming of surgeries in a hospital, repair of equipment or machinery in a workshop, among others. The objective of this study is to analyze the effect of the inclusion of several restrictions that negatively influence the production programming in a real manufacturing environment. For this purpose, an efficient Genetic Algorithm combined with a Local Search of Variable Neighborhood for problems of n tasks and m machines is introduced, minimizing the time of total completion of the tasks. The computational experiments carried out on a set of problem instances with different sizes of complexity show that the proposed hybrid metaheuristics achieves high quality solutions compared to the reported optimal cases. | spa |
dc.language.iso | eng | |
dc.publisher | Universidad de la Costa | spa |
dc.rights | info:eu-repo/semantics/closedAccess | spa |
dc.rights | CC0 1.0 Universal | spa |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | spa |
dc.subject | Hybrid genetic algorithm | spa |
dc.subject | Scheduling | spa |
dc.subject | Flow shop | spa |
dc.subject | Variable neighborhood search | spa |
dc.title | Optimization of flow shop scheduling through a hybrid genetic algorithm for manufacturing companies | spa |
dc.type | Pre-Publicación | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
dc.identifier.instname | Corporación Universidad de la Costa | spa |
dc.identifier.reponame | REDICUC - Repositorio CUC | spa |
dc.identifier.repourl | https://repositorio.cuc.edu.co/ | spa |
dc.type.coar | http://purl.org/coar/resource_type/c_816b | spa |
dc.type.content | Text | spa |
dc.type.driver | info:eu-repo/semantics/preprint | spa |
dc.type.redcol | http://purl.org/redcol/resource_type/ARTOTR | spa |
dc.type.version | info:eu-repo/semantics/acceptedVersion | spa |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
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