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dc.contributor.authorMejía Moncayo, Camilo
dc.contributor.authorGarzón Alvarado, Diego Alexander
dc.contributor.authorArroyo Osorio, José Manuel
dc.date.accessioned2020-01-08T19:04:25Z
dc.date.available2020-01-08T19:04:25Z
dc.date.issued2014-06-01
dc.identifierhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/5
dc.identifier10.18359/rcin.5
dc.identifier.urihttp://hdl.handle.net/10654/33060
dc.descriptionThis paper presents the mono-objective and multi-objective solution to the cell manufacturing layout problem using two new discrete hybrid algorithms based on bacterial chemotaxis and genetic algorithms. The proposed models simultaneously solve the issues that constitute the problem of the layout of manufacturing cells: the formation of the cells and the inter- and intra-cell layout, considering the clustering of cells, and the cost of transportation and material handling. The performance of the proposals was evaluated with benchmark problems of manufacturing cells, traveling salesman problem and a multi-objective version of knapsack problem. The mono-objective results were compared with GA, BFOA and Bacterial-GA, while the multi-objective results were compared with well-known algorithms NSGA2 and SPEA2, obtaining better performances in both cases.eng
dc.descriptionEste trabajo presenta la solución mono-objetivo y multi-objetivo del problema de la distribución de planta en celdas de manufactura a través de dos nuevos algoritmos híbridos discretos basados en quimiotaxis de bacterias y en algoritmos genéticos. Los modelos propuestos resuelven simultáneamente los dos inconvenientes que constituyen el problema de la distribución de planta en celdas de manufactura: la formación de las celdas y la distribución de planta intra e inter celdas, considerando el agrupamiento de las celdas y el costo de transporte y manipulación de materiales. El desempeño de las propuestas se evaluó con problemas de prueba de distribución de planta de celdas de manufactura, agente viajero (TSP) y el caso multi-objetivo del problema de las mochilas. Los resultados mono-objetivo se compararon con AG, BFOA y Bacterial-GA, mientras que los resultados multi-objetivo se compararon con los reconocidos algoritmos NSGA2 y SPEA2 en los que se obtuvo un mejor desempeño en los dos casos.spa
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dc.language.isospa
dc.publisherUniversidad Militar Nueva Granadaspa
dc.rightsDerechos de autor 2016 Ciencia e Ingeniería Neogranadinaspa
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0spa
dc.sourceCiencia e Ingenieria Neogranadina; Vol 24 No 1 (2014); 6-28eng
dc.sourceCiencia e Ingeniería Neogranadina; Vol. 24 Núm. 1 (2014); 6-28spa
dc.sourceCiencia e Ingeniería Neogranadina; v. 24 n. 1 (2014); 6-28por
dc.source1909-7735
dc.source0124-8170
dc.titleDiscrete methods base on bacterial chemotaxis and genetic algorithms to solve the cell manufacturing layout problemeng
dc.titleMétodos discretos basados en quimiotaxis de bacterias y algoritmos genéticos para solucionar el problema de la distribución de planta en celdas de manufactura.spa
dc.typeinfo:eu-repo/semantics/article
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dc.relation.referenceshttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/5/3
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dc.subject.proposalCell manufacturing layouteng
dc.subject.proposaloptimizationeng
dc.subject.proposalgenetic algorithmseng
dc.subject.proposalBFOAeng
dc.subject.proposalNSGA2eng
dc.subject.proposalSPEA2eng
dc.subject.proposalBCMOAeng
dc.subject.proposalhybridization.eng
dc.subject.proposalDistribución de planta de celdas de manufacturaspa
dc.subject.proposaloptimizaciónspa
dc.subject.proposalalgoritmos genéticosspa
dc.subject.proposalBFOAspa
dc.subject.proposalNSGA2spa
dc.subject.proposalSPEA2spa
dc.subject.proposalBCMOAspa
dc.subject.proposalhibridación.spa


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