Modelo de optimización no-lineal para redes de cadenas de suministro multiescalón a nivel táctico con demanda incierta

Abstract

In this work, a mixed integer nonlinear programming model is developed that determines the decisions to be taken for tactical planning in supply chains with uncertain demand. Initially, a review of the state of the art was developed to determine and analyze the research related to nonlinear optimization models focused on multiechelon supply chains for tactical planning. According to the results found, the mathematical components that subsequently determine the structure of three mathematical programming problems were proposed, with which a new way of modeling supply chains with acyclic networks for an established planning horizon is established and that allows to include different types of nonlinearities. The proposed MINLP models are non-convex and are solved through LINGO, BONMIN and COUENNE solvers, identifying that the first of these was the one that achieve the best solutions for the small and medium instances used. The results show that the proposed models offer relevant information for decisions to be made in supply chains within a given planning horizon, guaranteeing in certain cases a local optimum of the problem.