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dc.contributor.advisorNieto Isaza, Santiagospa
dc.contributor.authorMartinez Carranza, Cristian Andresspa
dc.contributor.authorMedina Turizo, Daniel Eduardospa
dc.date.accessioned2019-06-14T13:38:12Z
dc.date.available2019-06-14T13:38:12Z
dc.date.issued2014-07-15
dc.identifier.urihttp://hdl.handle.net/11323/4854spa
dc.description.abstractEn esta investigación se propone modelar una heurística para el análisis del desempeño de un modelo determinístico de ruteo de vehículos múltiples depósitos en un ambiente estocástico, en una empresa de acueducto del municipio de Uribia, Guajira, la cual se encarga de la distribución de agua potable a través de flotas de carro tanques para pequeñas comunidades indígenas del sector. Inicialmente se realiza una amplia revisión de la literatura de los VRP de tipo estocástico. Luego se realiza la modelación de un SMDVRP en tres etapas, la primera es un procedimiento de clusterización por depósitos bajo el criterio de mínima distancia recorrida, en la segunda se utiliza un método para la optimización de rutas de un (CVRP) basado en algoritmos de colonias de hormigas y en la tercera etapa se realiza la modelación estocástica del problema en base a dos variables de estudio. Por último se realiza un diseño de experimentos a los resultados obtenidos de la modelación del SVRP, para esto se definen unos factores de diseño con sus respectivos niveles, unos bloques de variabilidad y las variables de respuesta de interés del caso. El objetivo del diseño de experimentos para determinar qué factores son significativos de acuerdo con las variables de respuesta del caso y que ofrecen un mejor desempeño operacional del modelo de simulación estudiado. Los resultados obtenidos presentan un ahorro del 27% sobre los costos operacionales con respecto a la política de distribución actual que utiliza la empresa a la cual se hace el estudio.spa
dc.description.abstractThis research proposes a heuristic model for analyzing the performance of a deterministic model of multiple vehicle routing in a stochastic environment deposits, in a company aqueduct Uribia, Guajira, which is responsible for the distribution of drinking water by tank truck fleets for small indigenous communities sector. Initially an extensive literature review of stochastic VRP type is performed. SMDVRP modeling of a three-step is then performed, the first is a method of clustering on deposits under the criterion of minimum distance, the second a method of route optimization of a (CVRP) based algorithms used ant colonies and in the third stage the stochastic modeling of the problem is performed on the basis of two variables of the study. Finally, a design of experiments to the results of the modeling SVRP to this design factors at their respective levels are defined, and blocks of variable response variables of interest the case is performed. The objective of design of experiments to determine which factors are significant according to the response variables of the case and which offer better operational performance of the simulation model studied. The results show a 27% savings on operating costs compared to current distribution policy used by the company to which the study is done.spa
dc.language.isospa
dc.publisherUniversidad de la Costaspa
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/spa
dc.subjectAmbiente estocásticospa
dc.subjectClusterizaciónspa
dc.subjectColonias de hormigasspa
dc.subjectSimulación discretaspa
dc.subjectDiseño de experimentosspa
dc.subjectStochastic environmentspa
dc.subjectClusterizationspa
dc.subjectColonies of antsspa
dc.subjectDiscrete simulationspa
dc.subjectDesign of experimentsspa
dc.titleModelacion de una heuristica para el análisis del desempeño de un modelo deterministico de ruteo de vehículos multiples depósitos bajo un ambiente estocásticospa
dc.typeTrabajo de grado - Pregradospa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.publisher.programIngeniería Industrialspa
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Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands. Applied Soft Computing. Novoa, C., & Storer, R. (2008). An approximate dynamic programming approach for the vehicle routing problem with stochastic demands. European Journal of Operational Research. Olivera, A. (2004). Heurísticas para Problemas de Ruteo de Vehículos. Pandelis, D., Kyriakidis, E., & Dimitrakos, T. (2011). Single vehicle routing problems with a predefined customer sequence, compartmentalized load and stochastic demands. European Journal of Operational Research. Rocha, L., Gonzáles, C., & Orjuela, J. (2011). Una revisión del estado del arte del problema de ruteo de vehículos: Evolución histórica y métodos de solución. Secomandi , N. (2000). Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands. Computers & Operations Research. Taş, D., Gendreau, M., Dellaert, N., van Woensel, T., & de Kok, A. (2013). Vehicle Routing with Soft Time Windows and Stochastic Travel Times: A Column Generation and Branch-and-Price Solution Approach. European Journal of Operational Research. Tatarakis, A., & Minis , I. (2008). Stochastic single vehicle routing with a predefined customer sequence and multiple depot returns. European Journal of Operational Research. Van Woensel, T., Kerbache, L., Peremans, H., & Vandaele, N. (2001). A VEHICLE ROUTING PROBLEM WITH STOCHASTIC TRAVEL TIMES. Xiangyong Li, a., Peng Tian, a., & Stephen C.H Leung, b. (2010). Vehicle routing problems with the windows and stochastic travel and service times: Models and Algorithm. ELSEVIER. Yan, S., Chi, C.-J., & Tang, C.-H. (2005). Inter-city bus routing and timetable setting under stochastic demands. Transportation Research. Yan, S., Lin, J.-R., & Lai, C.-W. (2013). The planning and real-time adjustment of courier routing and scheduling under stochastic travel times and demands. Transporta tion Research.spa
dc.title.translatedModeling a heuristic for the analysis of the performance of a deterministic vehicle routing model multiple deposits under a stochastic environmentspa
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dc.type.driverinfo:eu-repo/semantics/bachelorThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TPspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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