Hybrid Optimization and Simulation Framework for Static and Dynamic Ambulance Allocation: A Case Study on Piedmont’s Emergency Medical Service

This thesis addresses the problem of ambulance allocation and relocation within the Emergency Medical Service (EMS) system of the Piedmont region. The aim of the study is to develop a methodological framework that integrates optimization techniques and dynamic simulation to support both strategic and operational planning decisions. Several location–allocation models were developed and compared based on efficiency, equity, and territorial coverage criteria, including a reliability-based formulation that accounts for ambulance availability and the clinical severity of calls. A dynamic simulation model was then implemented to evaluate the operational performance of the optimal static configurations, comparing a traditional return-to-base policy with a data-driven dynamic redeployment strategy constrained by realistic operational and shift conditions. The results show how different model formulations affect coverage and response-time metrics under variable demand conditions, highlighting the value of integrating optimization and simulation for more effective EMS system planning.