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Algoritmos genéticos aplicados al diseño de redes de distribución considerando demanda estocástica

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dc.contributor Cabrera Guerrero, Guillermo Nicolás
dc.creator Pizarro Díaz, Jessica Marianella
Fecha Ingreso dc.date.accessioned 2021-10-19T21:30:50Z
Fecha Disponible dc.date.available 2021-10-19T21:30:50Z
Fecha en Repositorio dc.date.issued 2021-10-19
Resumen dc.description <p>Este&nbsp; trabajo&nbsp; de&nbsp; t&iacute;tulo&nbsp; se&nbsp; basa&nbsp; en&nbsp; dise&ntilde;ar&nbsp; una&nbsp; red&nbsp; de&nbsp; distribuci&oacute;n,&nbsp; que&nbsp; abarque&nbsp; la&nbsp; toma&nbsp; de decisiones&nbsp; estrat&eacute;gicas,&nbsp; lo&nbsp; cual&nbsp; consiste&nbsp; en&nbsp; determinar&nbsp; la&nbsp; cantidad&nbsp; necesaria&nbsp;&nbsp;&nbsp; de instalaciones&nbsp; y&nbsp; donde&nbsp; localizarlas&nbsp; para&nbsp; proveer&nbsp; a&nbsp; los&nbsp; distintos&nbsp; clientes,&nbsp; de&nbsp; la&nbsp; forma&nbsp; m&aacute;s eficiente&nbsp; posible.&nbsp; Se&nbsp; tom&oacute;&nbsp; como&nbsp; base&nbsp; el&nbsp; modelo&nbsp; de&nbsp; localizaci&oacute;n&nbsp; Distribution&nbsp; Network Design&nbsp; with&nbsp; Risk&nbsp; Pooling&nbsp; (DNDRP),&nbsp; donde&nbsp; el&nbsp; problema&nbsp; apoya&nbsp; las&nbsp; decisiones&nbsp; estrat&eacute;gicas con las t&aacute;cticas, es decir, considera decisiones de control de inventario para brindar el nivel de&nbsp; servicio&nbsp; exigido&nbsp; por&nbsp; los&nbsp; clientes,&nbsp; manteniendo&nbsp; un&nbsp; stock&nbsp; de&nbsp; seguridad&nbsp; apropiado&nbsp; para satisfacer la demanda de los clientes. El problema fue resuelto mediante la metaheur&iacute;stica, Algoritmos&nbsp; Gen&eacute;ticos,&nbsp; la&nbsp; cual&nbsp; parte&nbsp; con&nbsp; una&nbsp; red&nbsp; generada&nbsp; aleatoriamente,&nbsp; utilizando&nbsp; la codificaci&oacute;n entera positiva. Esta poblaci&oacute;n est&aacute; formada por individuos, los cuales se ir&aacute;n cruzando&nbsp; y&nbsp; mutando&nbsp; iterativamente&nbsp; hasta&nbsp; arrojar&nbsp; una&nbsp; soluci&oacute;n&nbsp; factible&nbsp; para&nbsp; el&nbsp; problema. Los&nbsp; resultados&nbsp; obtenidos,&nbsp; si&nbsp; bien&nbsp; no&nbsp; fueron&nbsp; &oacute;ptimos,&nbsp; con&nbsp; respecto&nbsp; a&nbsp; otros&nbsp; m&eacute;todos&nbsp; de resoluci&oacute;n, arrojaron soluciones donde en algunos casos hubo una diferencia de tan solo un 0,1% de la &oacute;ptima encontrada.</p>
Resumen dc.description <p>This work is based on designing a distribution network, including strategic decisions, which is&nbsp; to&nbsp; determine&nbsp; the&nbsp; amount&nbsp; needed&nbsp; and&nbsp; where&nbsp; to&nbsp; locate&nbsp; facilities&nbsp; to&nbsp; provide&nbsp; individual customers,&nbsp; as&nbsp; efficiently&nbsp; as&nbsp; possible.&nbsp; Will&nbsp; be&nbsp; based&nbsp; on&nbsp; the&nbsp; model&nbsp; of&nbsp; localization Distribution&nbsp; Network&nbsp; Design&nbsp; with&nbsp; Risk&nbsp; Pooling&nbsp; (DNDRP),&nbsp; where&nbsp; the&nbsp; problem&nbsp; supports strategic decisions with the tactics, ie, considered decisions of inventory control to provide the&nbsp; level&nbsp; of&nbsp; service&nbsp; demanded&nbsp; by&nbsp; customers,&nbsp; keeping&nbsp; an&nbsp; appropriate&nbsp; safety&nbsp; stock&nbsp; to&nbsp; meet customer&nbsp; demand.&nbsp; The&nbsp; problem&nbsp; was&nbsp; solved&nbsp; by&nbsp; the&nbsp; metaheuristic,&nbsp; genetic&nbsp; algorithms,&nbsp; this start&nbsp; with&nbsp; a&nbsp; randomly&nbsp; generated&nbsp; network,&nbsp; using&nbsp; encoding&nbsp; entire&nbsp; positive.&nbsp; This&nbsp; population was comprised of individuals or chromosomes, which are iteratively crossing and mutating to produce a workable solution to the problem. The results obtained, were not optimal, with respect to exact methods of resolution. In some case the solutions was a difference of only 0.1% of the optimum found.</p>
Resumen dc.description last modification
Resumen dc.description Licenciado en Ciencias de la Ingeniería
Resumen dc.description Ingeniero Civil en Informáticatítulo
Resumen dc.description INGENIERIA CIVIL INFORMATICA
Resumen dc.description <p>Este&nbsp; trabajo&nbsp; de&nbsp; t&iacute;tulo&nbsp; se&nbsp; basa&nbsp; en&nbsp; dise&ntilde;ar&nbsp; una&nbsp; red&nbsp; de&nbsp; distribuci&oacute;n,&nbsp; que&nbsp; abarque&nbsp; la&nbsp; toma&nbsp; de decisiones&nbsp; estrat&eacute;gicas,&nbsp; lo&nbsp; cual&nbsp; consiste&nbsp; en&nbsp; determinar&nbsp; la&nbsp; cantidad&nbsp; necesaria&nbsp;&nbsp;&nbsp; de instalaciones&nbsp; y&nbsp; donde&nbsp; localizarlas&nbsp; para&nbsp; proveer&nbsp; a&nbsp; los&nbsp; distintos&nbsp; clientes,&nbsp; de&nbsp; la&nbsp; forma&nbsp; m&aacute;s eficiente&nbsp; posible.&nbsp; Se&nbsp; tom&oacute;&nbsp; como&nbsp; base&nbsp; el&nbsp; modelo&nbsp; de&nbsp; localizaci&oacute;n&nbsp; Distribution&nbsp; Network Design&nbsp; with&nbsp; Risk&nbsp; Pooling&nbsp; (DNDRP),&nbsp; donde&nbsp; el&nbsp; problema&nbsp; apoya&nbsp; las&nbsp; decisiones&nbsp; estrat&eacute;gicas con las t&aacute;cticas, es decir, considera decisiones de control de inventario para brindar el nivel de&nbsp; servicio&nbsp; exigido&nbsp; por&nbsp; los&nbsp; clientes,&nbsp; manteniendo&nbsp; un&nbsp; stock&nbsp; de&nbsp; seguridad&nbsp; apropiado&nbsp; para satisfacer la demanda de los clientes. El problema fue resuelto mediante la metaheur&iacute;stica, Algoritmos&nbsp; Gen&eacute;ticos,&nbsp; la&nbsp; cual&nbsp; parte&nbsp; con&nbsp; una&nbsp; red&nbsp; generada&nbsp; aleatoriamente,&nbsp; utilizando&nbsp; la codificaci&oacute;n entera positiva. Esta poblaci&oacute;n est&aacute; formada por individuos, los cuales se ir&aacute;n cruzando&nbsp; y&nbsp; mutando&nbsp; iterativamente&nbsp; hasta&nbsp; arrojar&nbsp; una&nbsp; soluci&oacute;n&nbsp; factible&nbsp; para&nbsp; el&nbsp; problema. Los&nbsp; resultados&nbsp; obtenidos,&nbsp; si&nbsp; bien&nbsp; no&nbsp; fueron&nbsp; &oacute;ptimos,&nbsp; con&nbsp; respecto&nbsp; a&nbsp; otros&nbsp; m&eacute;todos&nbsp; de resoluci&oacute;n, arrojaron soluciones donde en algunos casos hubo una diferencia de tan solo un 0,1% de la &oacute;ptima encontrada.</p>
Resumen dc.description <p>This work is based on designing a distribution network, including strategic decisions, which is&nbsp; to&nbsp; determine&nbsp; the&nbsp; amount&nbsp; needed&nbsp; and&nbsp; where&nbsp; to&nbsp; locate&nbsp; facilities&nbsp; to&nbsp; provide&nbsp; individual customers,&nbsp; as&nbsp; efficiently&nbsp; as&nbsp; possible.&nbsp; Will&nbsp; be&nbsp; based&nbsp; on&nbsp; the&nbsp; model&nbsp; of&nbsp; localization Distribution&nbsp; Network&nbsp; Design&nbsp; with&nbsp; Risk&nbsp; Pooling&nbsp; (DNDRP),&nbsp; where&nbsp; the&nbsp; problem&nbsp; supports strategic decisions with the tactics, ie, considered decisions of inventory control to provide the&nbsp; level&nbsp; of&nbsp; service&nbsp; demanded&nbsp; by&nbsp; customers,&nbsp; keeping&nbsp; an&nbsp; appropriate&nbsp; safety&nbsp; stock&nbsp; to&nbsp; meet customer&nbsp; demand.&nbsp; The&nbsp; problem&nbsp; was&nbsp; solved&nbsp; by&nbsp; the&nbsp; metaheuristic,&nbsp; genetic&nbsp; algorithms,&nbsp; this start&nbsp; with&nbsp; a&nbsp; randomly&nbsp; generated&nbsp; network,&nbsp; using&nbsp; encoding&nbsp; entire&nbsp; positive.&nbsp; This&nbsp; population was comprised of individuals or chromosomes, which are iteratively crossing and mutating to produce a workable solution to the problem. The results obtained, were not optimal, with respect to exact methods of resolution. In some case the solutions was a difference of only 0.1% of the optimum found.</p>
Formato dc.format PDF
Lenguaje dc.language spa
dc.rights autorizado
dc.source http://opac.pucv.cl/pucv_txt/txt-2500/UCH2888_01.pdf
Materia dc.subject Planificación de la producción
Materia dc.subject Producción
Materia dc.subject Software
Materia dc.subject DEMANDA
Materia dc.subject ALGORITMO GENETICO
Title dc.title Algoritmos genéticos aplicados al diseño de redes de distribución considerando demanda estocástica
Tipo dc.type texto


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