Two new models for redeployment of ambulances

We locate ambulance stations in four districts of Isfahan, Iran using MECRP.We formulate two models that specify how to assign ambulances to stations.The first model minimizes the total time traveled by ambulances.The second model minimizes the maximum time traveled by the ambulances.These models significantly reduce travel times and thus provide a good coverage. Nowadays, in all countries, public resources for healthcare are inadequate to meet the demands for the services. Therefore, policy makers should provide the most effective healthcare services to citizens within the limited available resources. During the past decades, lots of research using operations research techniques, tools, and theories has been applied to a wide range of problems in healthcare. Ambulance service planning is a branch of healthcare. Ambulance location and redeployment problems are considered two important issues in ambulance service planning. In these models, an attempt is made to maximize coverage in the districts and properly service the patients in emergency situations.In this paper, at first we use an existing model, named MECRP1Maximal Expected Coverage Relocation Problem.1, to locate ambulances in four districts of Isfahan, Iran. Then, we formulate a generalized assignment model with the aim of minimizing the total time traveled by ambulances. We also formulate a generalized bottleneck assignment model. The goal of this model is to minimize the maximum travel time. The proposed models specify the movement of the ambulances, using the out of MECRP determines the relocation of the ambulances in just one run for all possible combinations. In fact, each of these models specifies the movement of the ambulances from hospitals to stations or from stations to other stations based on its aim.In addition, to shed light on the merits of the proposed models, computational results on experimental data from Isfahan EMS agency are provided. The results, using these models, show travel times can be significantly reduced. By the end of this paper, the corresponding conclusions are expressed.

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