A backup double covering model and tabu search solution approach for locating emergency medical stations

The location planning of emergency medical service (EMS) stations is crucial, especially in populated cities with heavy traffic conditions like Istanbul. In this paper, we propose both a single-period and a multi-period problem, two variants of the well-known Maximal Covering Location Problem, which require two types of services in the location planning of the EMS stations. The objective of the single-period problem is to maximize the total population serviced within t1 and t2 minutes (t1 < t2) using two distinct emergency service stations where the total number of stations is limited. Similar to single-period problem, our objective in the multi-period problem is to maximize the total population serviced by two distinct stations within two different response time limits over a multi-period planning horizon. Our aim is to provide a backup station in case no ambulance is available in the closer station and develop a strategic plan that spans multiple periods. In order to solve these two problems, we propose a Tabu Search approach using different initialization approaches. We demonstrate the effectiveness of the proposed approach on randomly generated data. We also implement our approach to the case of Istanbul to determine the locations of EMS stations in the metropolitan area. Our computational study on both randomly generated data and real data for Istanbul shows that the proposed approach provides optimal/near-optimal solutions for the two problems.