Abstract

In this paper, we solved an ambulance location problem with a multi-objective framework considering the case of the study of Emergency Medical Service (EMS) of Antofagasta (Chile). Nowadays, in Antofagasta, the ambulances are located in bases that are not necessarily the optimal location achieving an estimated 67% of coverage under the 8 min not meeting the requirements dictated by the Chilean Ministry of Health. We used a multi-objective model considering mean response time, maximum response time, and the demand not covered. The model is solved using an iterative epsilon-constraint method to generate a Pareto set of efficient solutions. We considered historical data from the years 2015 and 2016 to gen-erate the demand and emergency nodes with a clustering algorithm. The results show improvements on all criteria of the multi-objective model, where we highlight a potential increment on coverage within 8 min from 67 to 99%. In order to test the new policy in a real setting, a pilot plan is proposed, which reaches 89% of coverage within 8 min.