A MILP facility location model with distance value adjustments for demand fulfillment using Google Maps

Abstract

In this article, a facility location model was designed to support logistics operations, considering service distance limitations for demand fulfillment and a list of candidate locations within a supply chain. Consequently, an allocation model was designed using Mixed-Integer Linear Programming (MILP), in which a finite number of demand nodes could be satisfied by a set of supply nodes, considering not only the costs related to these locations, but also restrictions aimed at improving the level of service based on distance. Besides, an integrated solution scheme was proposed that includes a macro in VBA language that calculates the distance between nodes using the web mapping service developed by Google Maps and solving the model through a branch and cut algorithm. Subsequently, a case study was executed, where the supply operation of an important Colombian retail company is analyzed. The results reflected positive effects not only on costs, but also on the prioritization of average distance traveled and on the satisfaction of store demand by distribution centers. Thus, the conditions in which the implementation of this model provides strategic benefits were verified, functioning as a tool to support decision making.