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A comparative analysis of genetic algorithms and QAP formulation for facility layout problem: An application in a real context
dc.contributor.author | Niebles F. | |
dc.contributor.author | Escobar I. | |
dc.contributor.author | Agudelo L. | |
dc.contributor.author | Jimenez G. | |
dc.date.accessioned | 2024-05-23T13:29:45Z | |
dc.date.available | 2024-05-23T13:29:45Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | ) Niebles, F., Escobar, I., Agudelo, L., Jimenez, G. A comparative analysis of genetic algorithms and QAP formulation for facility layout problem: An application in a real context (2016) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9713 LNCS, pp. 59-75. | es_CO |
dc.identifier.other | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010197315&doi=10.1007%2f978-3-319-41009-8_7&partnerID=40&md5=5966262e6379a13d469a624230aebac3 | |
dc.identifier.uri | http://hdl.handle.net/10818/60177 | |
dc.description | 16 páginas | es_CO |
dc.description.abstract | This paper considers the problem of locating facilities in manufac-turing of electrical, telecommunications and building products. This is known as the Facility Layout Problem (FLP). This NP-hard problem has been largely studied in the scientific literature, and exact and approximate (heuristic and meta-heuristic) approaches have been used mainly to optimize one or more objectives. However, most of these studies do not consider real applications. Hence, in this work, we propose the use of Sule’s Method and genetic algo-rithms, for facility layout in a real industry application in Colombia so that the total cost to move the required material between the facilities is minimized. As far as we know, this is the first work in which Sule’s Method and genetic algorithms are used simultaneously for this combinatorial optimization problem. Computational experiments are carried out comparing the proposed approach versus QAP formulation. Additionally, the proposed approach was tested using well-known datasets from the literature in order to assure its efficiency. © Springer International Publishing Switzerland 2016. | en |
dc.format | application/pdf | es_CO |
dc.language.iso | eng | es_CO |
dc.publisher | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | es_CO |
dc.relation.ispartofseries | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9713 LNCS p. 59-75 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.source | Universidad de La Sabana | es_CO |
dc.source | Intellectum Repositorio Universidad de La Sabana | es_CO |
dc.subject.other | Facility layout problem | en |
dc.subject.other | Genetic algorithms | en |
dc.subject.other | Quadratic assignment problem | en |
dc.title | A comparative analysis of genetic algorithms and QAP formulation for facility layout problem: An application in a real context | en |
dc.type | book part | es_CO |
dc.type.hasVersion | publishedVersion | es_CO |
dc.rights.accessRights | openAccess | es_CO |
dc.identifier.doi | 10.1007/978-3-319-41009-8_7 |
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