Optimization of Humanitarian Aid Resource Distribution Time Through Mixed Integer Linear Programming

Abstract

This paper develops a post-disaster response model that jointly optimizes the distribution time of essential humanitarian aid goods (i.e.: medicines, water and food) from temporary warehouses to points of demand, and the satisfaction of the needs of the affected people. First, the travel time is measured through a Google Maps API Distance Matrix tool, based on the route between geo-referenced positions and the current vehicle density. Then, a model is built through Mixed Integer Linear Programming (MILP) to minimize the travel time to the demand points. Finally, the model is applied in a case study for the city of Chosica, Peru, to determine its effectiveness.