Problema de inventarios coordinados, entre una bodega y N minoristas, considerando múltiples productos en un escenario de demanda estocástica
This document is about a multi-product policy in one warehouse systems and N coordinated retailers. The methods of solution implemented in this work assume a deterministic as well as stochastic behavior of the demand, having the stochastic solution allows the scope of the project to have variations...
| Autor Principal: | Chavarro Santana, Nicolás |
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| Otros Autores: | Camelo Prieto, Ivan David, Atehortua Galvis, Santiago |
| Formato: | Trabajo de grado |
| Publicado: |
Pontificia Universidad Javeriana
2018
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| Materias: | |
| Acceso en línea: |
http://hdl.handle.net/10554/36374 |
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| Sumario: |
This document is about a multi-product policy in one warehouse systems and N coordinated retailers.
The methods of solution implemented in this work assume a deterministic as well as stochastic behavior of the demand, having the stochastic solution allows the scope of the project to have variations of demand with known distributions, in order to have dynamic solutions that come close to reality.
The main objective of the work is to design a solution for the problem of coordinated inventories, between a warehouse and N retailers, which considers multiple products, with stochastic demand; having as specific objectives i) Develop a cost function for a problem of coordinated inventories between a warehouse and N retailers that takes into account multiple products, with stochastic demand, ii) Design a deterministic solution for the problem , iii) Measure the performance of the deterministic technique in scenarios with demand variability, iv) Integrate a Monte Carlo simulation and the solution technique designed to solve the stochastic version of the problem, and v) Evaluate the impact of the solution method proposed by the Monte Carlo simulation and management indicators.
With the mathematical models, the factors of interest were defined with each of their levels in order to generate different instances to evaluate the problem in different situations. In order to find the lowest possible cost, we program a tabu search metaheuristic in VBA for Microsoft Excel, executing it for each one of the generated instances for both policies. With the final results a simulation was carried out which generates 1000 random demands and compares the two policies using the stochastic function in order to determine which of the two policies is better. With the results obtained the document presents an important conclusion; Taking both versions, the stochastic solution improves between 5.4% and 10%. |
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