Aplicación de un Algoritmo Genético para la Solución de Modelos de Inventario Estocásticos

Abstract

Generally getting optimal policies to inventory management is based on analytical methods from the research operations field. The models that represent these policies can become so complex than their solution by means of analytical model can be difficult and inefficient. This paper proposes an altemative to solve stochastic inventory models for which usually applied methods are not feasible. Here the use of a genetic algorithm to solve this problem is analy sed. This computational technique of the artificial intelligence field is applied along with a process simulator that helps to carry out the search of a satisfactory solution.