Model of routing for raw milk collection using genetic algorithms

The article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genet...

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Autores:
Correa Valencia, Maritza
Rosales Vásquez, Ricardo Edmundo
Tipo de recurso:
Article of journal
Fecha de publicación:
2014
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
spa
eng
OAI Identifier:
oai:red.uao.edu.co:10614/12145
Acceso en línea:
http://red.uao.edu.co//handle/10614/12145
Palabra clave:
Modelo de ruteo
Métodos metaheurísticos
Algoritmos genéticos
Model of routing
Metaheuristic methods
Genetic algorithms
Genetic algorithms
Modelo de roteamento
Métodos meta heurísticos
Algoritmos genéticos
Rights
openAccess
License
Derechos Reservados - Universidad ICESI, 2014
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dc.title.eng.fl_str_mv Model of routing for raw milk collection using genetic algorithms
dc.title.alternative.spa.fl_str_mv Modelo de ruteo para recolección de leche cruda usando algoritmos genéticos
dc.title.alternative.por.fl_str_mv Modelo de roteamento para coleta de leite cru utilizando algoritmos genéticos
title Model of routing for raw milk collection using genetic algorithms
spellingShingle Model of routing for raw milk collection using genetic algorithms
Modelo de ruteo
Métodos metaheurísticos
Algoritmos genéticos
Model of routing
Metaheuristic methods
Genetic algorithms
Genetic algorithms
Modelo de roteamento
Métodos meta heurísticos
Algoritmos genéticos
title_short Model of routing for raw milk collection using genetic algorithms
title_full Model of routing for raw milk collection using genetic algorithms
title_fullStr Model of routing for raw milk collection using genetic algorithms
title_full_unstemmed Model of routing for raw milk collection using genetic algorithms
title_sort Model of routing for raw milk collection using genetic algorithms
dc.creator.fl_str_mv Correa Valencia, Maritza
Rosales Vásquez, Ricardo Edmundo
dc.contributor.author.none.fl_str_mv Correa Valencia, Maritza
Rosales Vásquez, Ricardo Edmundo
dc.subject.proposal.spa.fl_str_mv Modelo de ruteo
Métodos metaheurísticos
Algoritmos genéticos
topic Modelo de ruteo
Métodos metaheurísticos
Algoritmos genéticos
Model of routing
Metaheuristic methods
Genetic algorithms
Genetic algorithms
Modelo de roteamento
Métodos meta heurísticos
Algoritmos genéticos
dc.subject.proposal.eng.fl_str_mv Model of routing
Metaheuristic methods
Genetic algorithms
Genetic algorithms
dc.subject.proposal.por.fl_str_mv Modelo de roteamento
Métodos meta heurísticos
Algoritmos genéticos
description The article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genetic algorithm. The results show that the routes obtained with the implementation of the genetic algorithm are feasible in terms of time and visited nodes, demonstrating the potential of this tool. The costs obtained by this method differ from the current methods by about 3%, which is within the range reported in the literature
publishDate 2014
dc.date.issued.none.fl_str_mv 2014-12
dc.date.accessioned.none.fl_str_mv 2020-03-24T12:16:44Z
dc.date.available.none.fl_str_mv 2020-03-24T12:16:44Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.issn.none.fl_str_mv 1692-5238
dc.identifier.uri.none.fl_str_mv http://red.uao.edu.co//handle/10614/12145
dc.identifier.instname.none.fl_str_mv Universidad Autónoma de Occidente
dc.identifier.reponame.spa.fl_str_mv Repositorio Educativo Digital
identifier_str_mv 1692-5238
Universidad Autónoma de Occidente
Repositorio Educativo Digital
url http://red.uao.edu.co//handle/10614/12145
dc.language.iso.spa.fl_str_mv spa
dc.language.iso.eng.fl_str_mv eng
language spa
eng
dc.relation.spa.fl_str_mv Sistemas & Telemática. Volumen 12, número 31, 2014; páginas 77- 87
dc.relation.citationendpage.none.fl_str_mv 87
dc.relation.citationissue.none.fl_str_mv 31
dc.relation.citationstartpage.none.fl_str_mv 77
dc.relation.citationvolume.none.fl_str_mv 12
dc.relation.cites.spa.fl_str_mv Correa Valencia, M., Rosales Vásquez, R. E. (2014) Model of routing for raw milk collection using genetic algorithms. Sistemas & Telemática. 12(31), 77-87. http://red.uao.edu.co//handle/10614/12145
dc.relation.ispartofjournal.spa.fl_str_mv Sistemas & Telemática
dc.relation.references.none.fl_str_mv Alegre, J., Laguna, M., & Pacheco, J. (2007). Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts. European Journal of Operational Research, 179(3), 736-746
Baker, B. M., & Ayechew, M.A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5) 787-800
Claassen, G. D. & Hendriks, T.B. (2007). An application of special ordered sets to a periodic milk collection problem. European Journal of Operational Research, 180(2), 754-769
Duarte, A. (2007). Metaheurísticas. Madrid: Dykinson
García-Najera, A. & Bullinaria, J. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287
Jozefowiez, N., Sernet, F., & Talbi, E.-G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.
Laudon, K.C., & Laudon, J.P. (2004). Sistemas de información gerencial: administración de la empresa digital. (trans. A. Núñez). México DF: Pearson
Maroto, C., Alcaraz, J., & Ruiz, R. (2002). Investigación operativa: modelos y técnicas de optimización. Valencia: Universidad Politécnica de Valencia.
Nagata, Y., Bräysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737
Oppen, J. & Lokketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213-3229
Robusté, F. & Galván, D. (2005). e-logistics. Barcelona: Universidad Politécnica de Catalunya
Sigurd, M., Pisinger, D., & Sig, M. (2004). Scheduling transportation of live animals. Transportation Science, 38(2), 197-209
Sterzik, S. & Kopfer, H. (2013). A tabu search heuristic for the inland container transportation problem. Computers and Operations Research, 40(4), 953-962
Tarantilis, C. D., & Kiranoudis, C. T. (2005). Operational research and food logistics. Journal of Food Engineering, 70(3), 253-255
Vansteenwegen, P., Souffriau, W., & Sörensen, K. (2010). Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated ARC routing with soft time windows. Computers and Operations Research, 37(11), 1870-1876
dc.rights.spa.fl_str_mv Derechos Reservados - Universidad ICESI, 2014
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https://creativecommons.org/licenses/by-nc-nd/4.0/
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spelling Correa Valencia, Maritzavirtual::1367-1Rosales Vásquez, Ricardo Edmundo044589f589d777ef5614773fa97951b12020-03-24T12:16:44Z2020-03-24T12:16:44Z2014-121692-5238http://red.uao.edu.co//handle/10614/12145Universidad Autónoma de OccidenteRepositorio Educativo DigitalThe article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genetic algorithm. The results show that the routes obtained with the implementation of the genetic algorithm are feasible in terms of time and visited nodes, demonstrating the potential of this tool. The costs obtained by this method differ from the current methods by about 3%, which is within the range reported in the literatureEl artículo presenta la utilización de un método metaheurístico –algoritmos genéticos– para la evaluación de un modelo de rutas de recolección de leche cruda. Se implemen tó un modelo a partir de datos reales, recolectados por medio de trabajo de campo, siguiendo el método del «problema del agente viajero», usando el toolbox de algoritmos genéticos de Matlab®. Los resultados evidencian que las rutas obtenidas con la implementación del algoritmo genético son viables en cuanto a tiempo y nodos visitados, lo que demuestra el potencial de esta herramienta. Los costos obtenidos por este método difieren de los actuales en alrededor de 3%, valor que está dentro de los márgenes reportados en la literaturaO artigo mostra o uso de um método meta heu rístico - algoritmos genéticos - para avaliar um padrão de rotas de coleta de leite cru. Foi implementado um modelo baseado em dados reais, coletados por meio de trabalho de campo, se guindo o método do “Problema do Caixeiro Viajante”, usando os algoritmos genéticos da caixa de ferramentas Matlab®. Os resultados mostram que as rotas obtidas com a implementação do algoritmo genético são viáveis em termos de tempo e de nós visitados, demonstrando assim o potencial desta ferramenta. Os custos obtidos por este método diferem dos atuais em aproxi madamente 3%, o que está dentro do intervalo referido na li teraturaapplication/pdf11 páginasspaengUniversidad ICESISistemas & Telemática. Volumen 12, número 31, 2014; páginas 77- 8787317712Correa Valencia, M., Rosales Vásquez, R. E. (2014) Model of routing for raw milk collection using genetic algorithms. Sistemas & Telemática. 12(31), 77-87. http://red.uao.edu.co//handle/10614/12145Sistemas & TelemáticaAlegre, J., Laguna, M., & Pacheco, J. (2007). Optimizing the periodic pick-up of raw materials for a manufacturer of auto parts. European Journal of Operational Research, 179(3), 736-746Baker, B. M., & Ayechew, M.A. (2003). A genetic algorithm for the vehicle routing problem. Computers & Operations Research, 30(5) 787-800Claassen, G. D. & Hendriks, T.B. (2007). An application of special ordered sets to a periodic milk collection problem. European Journal of Operational Research, 180(2), 754-769Duarte, A. (2007). Metaheurísticas. Madrid: DykinsonGarcía-Najera, A. & Bullinaria, J. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287Jozefowiez, N., Sernet, F., & Talbi, E.-G. (2009). An evolutionary algorithm for the vehicle routing problem with route balancing. European Journal of Operational Research, 195(3), 761-769.Laudon, K.C., & Laudon, J.P. (2004). Sistemas de información gerencial: administración de la empresa digital. (trans. A. Núñez). México DF: PearsonMaroto, C., Alcaraz, J., & Ruiz, R. (2002). Investigación operativa: modelos y técnicas de optimización. Valencia: Universidad Politécnica de Valencia.Nagata, Y., Bräysy, O., & Dullaert, W. (2010). A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 37(4), 724-737Oppen, J. & Lokketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213-3229Robusté, F. & Galván, D. (2005). e-logistics. Barcelona: Universidad Politécnica de CatalunyaSigurd, M., Pisinger, D., & Sig, M. (2004). Scheduling transportation of live animals. Transportation Science, 38(2), 197-209Sterzik, S. & Kopfer, H. (2013). A tabu search heuristic for the inland container transportation problem. Computers and Operations Research, 40(4), 953-962Tarantilis, C. D., & Kiranoudis, C. T. (2005). Operational research and food logistics. Journal of Food Engineering, 70(3), 253-255Vansteenwegen, P., Souffriau, W., & Sörensen, K. (2010). Solving the mobile mapping van problem: A hybrid metaheuristic for capacitated ARC routing with soft time windows. Computers and Operations Research, 37(11), 1870-1876Derechos Reservados - Universidad ICESI, 2014https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Model of routing for raw milk collection using genetic algorithmsModelo de ruteo para recolección de leche cruda usando algoritmos genéticosModelo de roteamento para coleta de leite cru utilizando algoritmos genéticosArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTREFinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Modelo de ruteoMétodos metaheurísticosAlgoritmos genéticosModel of routingMetaheuristic methodsGenetic algorithmsGenetic algorithmsModelo de roteamentoMétodos meta heurísticosAlgoritmos genéticosPublicationecc91e59-ce00-443d-bce6-ce85014e9629virtual::1367-1ecc91e59-ce00-443d-bce6-ce85014e9629virtual::1367-1https://scholar.google.com/citations?user=15MGkAQAAAAJ&hl=envirtual::1367-10000-0001-8464-2673virtual::1367-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001435997virtual::1367-1CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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