Thesis APLICACIÓN DE UN SISTEMA JERÁRQUICO ESTOCÁSTICO CON RECURSOS PARA EL PROBLEMA DE LA PLANIFICACIÓN DE LA PRODUCCIÓN CONDICIONADO POR ESCENARIOS DE DEMANDA INCIERTOS.
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Date
2009-11
Authors
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Program
DEPARTAMENTO DE INDUSTRIAS. INGENIERÍA CIVIL INDUSTRIAL
Campus
Campus Vitacura, Santiago
Abstract
En este trabajo se busca resolver y validar, una aproximación jerárquica, para el problema de la planificación de la producción (“Hierarchical Production Planning”: HPP), sujeto a la inserción de incertidumbre sobre la demanda. En una primera etapa se revisa el diseño jerárquico propuesto en Bitran y Hax (1977) y en Ortiz (2005), para una modelación determinista. Seguido a esto se examina el esquema jerárquico propuesto en Albornoz y Ortiz (2008).en donde se desarrolla una modelación estocástico con recurso para problemas con escenarios inciertos de demanda. El sistema HPP presentado para los casos determinista y estocástico se estructura por tres niveles, en donde el primer nivel consiste en un problema de planificación agregado, el segundo a un problema de desagregación de productos y el tercero a un problema de desagregación de producción mensual en semanal. La resolución del problema jerárquico de la planificación de la producción desarrollado, se basa en información de producción de una empresa manufacturera de artículos de línea blanca, ejecutando el problema para representaciones deterministas y bajo incertidumbre, utilizando como base del modelo estocástico, la representación determinista. El problema bajo incertidumbre desarrollado consiste en un modelo estocástico, con recurso, multietapa representado por medio de un árbol simétrico compuesto por 9 escenarios. La construcción de los algoritmos ocupados para la resolución de este problema se desarrolló por medio del lenguaje AMPL y fueron resueltos vía los programas iterativos CPLEX 11.0 y MINOS 5.51, en un computador Pentium IV de 2.66 [GHz] Finalmente, se presenta la validación del valor estocástico obtenido por medio del cálculo de los indicadores EVPI y VSS, los cuales entregan la significancia de la solución estocástica en comparación a la determinista.
In this memory seeks to resolve and validate a Hierarchical Production Planning (HPP) approximation to the problem of production planning, dependant on the insertion of uncertainty on the demand. In the first stage, there is a revision of the hierarchical design as proposed by Bitran and Hax (1977) and in Ortiz (2005) for deterministic modeling. This is followed by an examination of the hierarchical scheme proposed in Albornoz and Ortiz (2008), where stochastic modeling with resources for problems with uncertain demand scenarios is developed. The HPP system that is presented for stochastic and deterministic cases is structured in three levels, where the first level is an aggregated planning problem, the second level is a problem of disaggregation of products, and the third level is a problem of disaggregation of monthly to weekly production. The resolution of the hierarchical production planning problem developed is based on production information from an organization that manufactures electrical household appliances, executing the problem for deterministic representations and under incertitude, using as base for the stochastic model the deterministic representation. The problem under incertitude developed consists of a stochastic model with resource, multistage represented by a symmetrical tree composed of 9 scenarios. The construction of the algorithms used for the resolution of this problem was done through AMPL language, and they were resolved through CPLEX 11.0 and MINOS 5.51 iterative programs on a Pentium IV 2.66 [GHz] computer. Finally, there is a validation of the stochastic value obtained through a calculation of the EVPI and VSS indicators, which give the significance of the stochastic solution in comparison to the deterministic one.
In this memory seeks to resolve and validate a Hierarchical Production Planning (HPP) approximation to the problem of production planning, dependant on the insertion of uncertainty on the demand. In the first stage, there is a revision of the hierarchical design as proposed by Bitran and Hax (1977) and in Ortiz (2005) for deterministic modeling. This is followed by an examination of the hierarchical scheme proposed in Albornoz and Ortiz (2008), where stochastic modeling with resources for problems with uncertain demand scenarios is developed. The HPP system that is presented for stochastic and deterministic cases is structured in three levels, where the first level is an aggregated planning problem, the second level is a problem of disaggregation of products, and the third level is a problem of disaggregation of monthly to weekly production. The resolution of the hierarchical production planning problem developed is based on production information from an organization that manufactures electrical household appliances, executing the problem for deterministic representations and under incertitude, using as base for the stochastic model the deterministic representation. The problem under incertitude developed consists of a stochastic model with resource, multistage represented by a symmetrical tree composed of 9 scenarios. The construction of the algorithms used for the resolution of this problem was done through AMPL language, and they were resolved through CPLEX 11.0 and MINOS 5.51 iterative programs on a Pentium IV 2.66 [GHz] computer. Finally, there is a validation of the stochastic value obtained through a calculation of the EVPI and VSS indicators, which give the significance of the stochastic solution in comparison to the deterministic one.
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Keywords
PLANIFICACION DE LA PRODUCCION -- MODELOS MATEMATICOS