VRP model with time window, multiproduct and multidepot

With the increase in the transfer of products in supply chains, the organization of routes requires a complex allocation insofar as different environmental variables are considered, and VRP models are an efficient tool for the solution of routing systems of low, medium and high complexity. In this p...

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Autores:
Ruiz-Meza, José
Montes, Isaid
Pérez, Arnoldo
Ramos-Márquez, María
Tipo de recurso:
Fecha de publicación:
2020
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/9537
Acceso en línea:
https://hdl.handle.net/20.500.12585/9537
http://jase.tku.edu.tw/articles/jase-202006-23-2-0008
Palabra clave:
Pareto analysis
Mathematical model
Vehicle routing
Optimization
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv VRP model with time window, multiproduct and multidepot
title VRP model with time window, multiproduct and multidepot
spellingShingle VRP model with time window, multiproduct and multidepot
Pareto analysis
Mathematical model
Vehicle routing
Optimization
title_short VRP model with time window, multiproduct and multidepot
title_full VRP model with time window, multiproduct and multidepot
title_fullStr VRP model with time window, multiproduct and multidepot
title_full_unstemmed VRP model with time window, multiproduct and multidepot
title_sort VRP model with time window, multiproduct and multidepot
dc.creator.fl_str_mv Ruiz-Meza, José
Montes, Isaid
Pérez, Arnoldo
Ramos-Márquez, María
dc.contributor.author.none.fl_str_mv Ruiz-Meza, José
Montes, Isaid
Pérez, Arnoldo
Ramos-Márquez, María
dc.subject.keywords.spa.fl_str_mv Pareto analysis
Mathematical model
Vehicle routing
Optimization
topic Pareto analysis
Mathematical model
Vehicle routing
Optimization
description With the increase in the transfer of products in supply chains, the organization of routes requires a complex allocation insofar as different environmental variables are considered, and VRP models are an efficient tool for the solution of routing systems of low, medium and high complexity. In this paper, we developed a vehicle routing model with hard time window, multidepot, multiproduct and heterogeneous fleet for the minimization of the distance travelled. We applied the model to a case study of a company that distributes water bottles and bales in which we made a new distribution of delivery schedules by order applied Pareto analysis. We obtained optimal computational results using exact methods in a very short computational time and minimizing the distance to 35.08% of the current route.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-11-04T21:02:55Z
dc.date.available.none.fl_str_mv 2020-11-04T21:02:55Z
dc.date.issued.none.fl_str_mv 2020-02-15
dc.date.submitted.none.fl_str_mv 2020-10-03
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dc.identifier.citation.spa.fl_str_mv Ruiz-Meza, J., Montes, I., Pérez, A., & Ramos-Márquez, M. (2020). VRP Model with Time Window, Multiproduct and Multidepot. Journal of Applied Science and Engineering, 23(2), 239-247. https://doi.org/10.6180/jase.202006_23(2).0008
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dc.identifier.doi.none.fl_str_mv 10.6180/jase.202006_23(2).0008
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Ruiz-Meza, J., Montes, I., Pérez, A., & Ramos-Márquez, M. (2020). VRP Model with Time Window, Multiproduct and Multidepot. Journal of Applied Science and Engineering, 23(2), 239-247. https://doi.org/10.6180/jase.202006_23(2).0008
10.6180/jase.202006_23(2).0008
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/9537
http://jase.tku.edu.tw/articles/jase-202006-23-2-0008
dc.language.iso.spa.fl_str_mv eng
language eng
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dc.format.extent.none.fl_str_mv 9 páginas
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dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Journal of Applied Science and Engineering, Vol. 23, No 2, Page 239-247
institution Universidad Tecnológica de Bolívar
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spelling Ruiz-Meza, Joséc98cae4b-3334-4570-8eb3-9a5fc32e24a2Montes, Isaidbd19fb3f-c890-42ff-9b2a-b2b158099188Pérez, Arnoldoee0e130c-db4f-4c45-a4e6-801368f9a363Ramos-Márquez, Maríaeec7c004-0d7d-4c95-b4bd-73eb1cb578af2020-11-04T21:02:55Z2020-11-04T21:02:55Z2020-02-152020-10-03Ruiz-Meza, J., Montes, I., Pérez, A., & Ramos-Márquez, M. (2020). VRP Model with Time Window, Multiproduct and Multidepot. Journal of Applied Science and Engineering, 23(2), 239-247. https://doi.org/10.6180/jase.202006_23(2).0008https://hdl.handle.net/20.500.12585/9537http://jase.tku.edu.tw/articles/jase-202006-23-2-000810.6180/jase.202006_23(2).0008Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarWith the increase in the transfer of products in supply chains, the organization of routes requires a complex allocation insofar as different environmental variables are considered, and VRP models are an efficient tool for the solution of routing systems of low, medium and high complexity. In this paper, we developed a vehicle routing model with hard time window, multidepot, multiproduct and heterogeneous fleet for the minimization of the distance travelled. We applied the model to a case study of a company that distributes water bottles and bales in which we made a new distribution of delivery schedules by order applied Pareto analysis. We obtained optimal computational results using exact methods in a very short computational time and minimizing the distance to 35.08% of the current route.9 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Journal of Applied Science and Engineering, Vol. 23, No 2, Page 239-247VRP model with time window, multiproduct and multidepotinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Pareto analysisMathematical modelVehicle routingOptimizationCartagena de IndiasMaestrosBaldacci, R., Toth, P., & Vigo, D. (2007). Recent advances in vehicle routing exact algorithms. 4OR, 5(4), 269–298. https://doi.org/10.1007/s10288-007-0063-3Bektaş, T., & Laporte, G. (2011). The Pollution-Routing Problem. Transportation Research Part B, 45, 1232–1250. https://doi.org/10.1016/j.trb.2011.02.004Belgin, O., Karaoglan, I., & Altiparmak, F. (2018). Two-echelon vehicle routing problem with simultaneous pickup and delivery: Mathematical model and heuristic approach. Computers and Industrial Engineering, 115(March 2016), 1–16. https://doi.org/10.1016/j.cie.2017.10.032Blum, C. (2012). Hybrid metaheuristics in combinatorial optimization: A tutorial. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7505 LNCS(6), 1–10. https://doi.org/10.1007/978-3-642-33860-1_1oussaïd, I., Lepagnot, J., & Siarry, P. (2013). A survey on optimization metaheuristics. Information Sciences, 237, 82–117. https://doi.org/10.1016/j.ins.2013.02.041Clarke, G., & Wright, J. W. W. (1964). Scheduling of Vehicles from a Central Depot to a Number of Delivery Points. Operations Research, 12(4), 568–581. https://doi.org/10.1287/opre.12.4.568Cordeau, J. F., Laporte, G., Savelsbergh, M. W. P., & Vigo, D. (2007). Vehicle Routing. In Handbooks in Operations Research and Management Science (Vol. 14, pp. 367–428). https://doi.org/10.1016/S0927-0507(06)14006-2Golden, B. L., Magnanti, T. L., & Nguyan, H. G. (1972). Implementing vehicle routing algorithms. Networks, 7, 113–148.Grötschel, M., & Holland, O. (1991). Solution of large-scale symmetric travelling salesman problems. Mathematical Programming, 51(1–3), 141–202. https://doi.org/10.1007/BF01586932Iqbal, S., Kaykobad, M., & Rahman, M. S. (2015). Solving the multi-objective Vehicle Routing Problem with Soft Time Windows with the help of bees. Swarm and Evolutionary Computation, 24, 50–64. https://doi.org/10.1016/j.swevo.2015.06.001Isaza, S. N. (2012). Desarrollo y Codificación de un Modelo Matemático para la Optimización de un Problema de Ruteo de Vehículos con Múltiples DepósitosJourdan, L., Basseur, M., & Talbi, E. G. (2009). Hybridizing exact methods and metaheuristics: A taxonomy. European Journal of Operational Research, 199(3), 620–629. https://doi.org/10.1016/j.ejor.2007.07.035Kalayci, C. B., & Kaya, C. (2016). An ant colony system empowered variable neighborhood search algorithm for the vehicle routing problem with simultaneous pickup and delivery. Expert Systems with Applications, 66, 163–175. https://doi.org/10.1016/j.eswa.2016.09.017Kara, I., Kara, B., & Yetis, M. (2007). Energy Minimizing Vehicle Routing Problem. In Software Engineering and Formal Methods. https://doi.org/10.1021/pr800044qKoç, Ç., Bektaş, T., Jabali, O., & Laporte, G. (2016). Thirty years of heterogeneous vehicle routing. European Journal of Operational Research, 249(1), 1–21. https://doi.org/10.1016/j.ejor.2015.07.020Kumar, S. N., & Panneerselvam, R. (2012). A Survey on the Vehicle Routing Problem and Its Variants. Intelligent Information Management, 04(03), 66–74. https://doi.org/10.4236/iim.2012.43010Laporte, G., Nobert, Y., & Arpin, D. (1986). An exact algorithm for solving a capacitated location-routing problem. Annals of Operations Research, 6(9), 291–310. https://doi.org/10.1007/BF02023807Laporte, Gilbert. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3), 345–358. https://doi.org/10.1016/0377-2217(92)90192-CLaporte, Gilbert, Louveaux, F. V, & Mercure, H. (1994). A Priori Optimization of the Probabilistic Traveling Salesman Problem. Operations Research, 42(3), 543–549. Retrieved from http://www.jstor.org/stable/171892Lüer, A., Benavente, M., Bustos, J., & Venegas, B. (2009). El problema de rutas de vehŕculos: Extensiones y métodos de resolución estado del arte. CEUR Workshop Proceedings, 558(JANUARY 2009).Montoya-Torres, J. R., López Franco, J., Nieto Isaza, S., Felizzola Jiménez, H., & Herazo-Padilla, N. (2015). A literature review on the vehicle routing problem with multiple depots. Computers and Industrial Engineering, 79, 115–129. https://doi.org/10.1016/j.cie.2014.10.029Olivera, A. (2004). Heurísticas para problemas de ruteo de vehículos. Instituto de Computacion - Facultad de Ingenieria., 63.Parthanadee, P., & Logendran, R. (2002). Multi-Product Multi-Depot Periodic Distribution ProblemPérez-Rodríguez, R., & Hernández-Aguirre, A. (2019). A hybrid estimation of distribution algorithm for the vehicle routing problem with time windows. Computers and Industrial Engineering, 130(February), 75–96. https://doi.org/10.1016/j.cie.2019.02.017Puente-Riofrío, M. ;, & Andrade-Domínguez, F. (2016). Relación entre la diversificación de productos y la rentabilidad empresarial. Revista Ciencia UNEMI, 9(18), 73–80.Renaud, J., Laporte, G., & Boctor, F. F. (1996). 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Estudio del problema de ruteo de vehículos con balance de carga :Aplicación de la meta-heurística Búsqueda Tabú. Retrieved from http://hdl.handle.net/10818/9798Solomon, M., & Desrosiers, J. (1988). Time Window Constrained Routing and Scheduling Problems. Transportation Science, 22(1), 1–13. Retrieved from http://www.jstor.org/stable/25768291Sombuntham, P., & Kachitvichyanukul, V. (2010). Multi-depot vehicle routing problem with pickup and delivery requests. AIP Conference Proceedings, 1285(December), 71–85. https://doi.org/10.1063/1.3510581Wilson, N. H. M., Sussman, J. M., Wong, H.-K., & Higonnet, T. (1971). Scheduling algorithms for a dial-a-ride system. Massachusetts Institute of Technology. Urban Systems Laboratory.Young, R. R., & Esqueda, P. (2005). Vulnerabilidades de la cadena de suministros: consideraciones para el caso de América Latina. Academia. Revista Latinoamericana de Administración, (34), 63–78. 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