Accelerating Emergency Response: An Optimized Ambulance Dispatch Model for Manhattan

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This project examines three optimization strategies to minimise response of ambulance dispatch in Manhattan: a min-sum model, a min-max model, and robust versions of both. The min-sum model seeks to minimize the total response time across all emergency incidents, while the min-max model aims to minimize the maximum response time to ensure equitable service delivery. The robust models address uncertainties in real-world scenarios by incorporating potential variations in station capacities and incident demands. By comparing these approaches, we aim to identify the most effective and resilient deployment strategy for emergency medical services (EMS). Our mathematical models account for practical constraints and potential fluctuations in parameters. This comparative analysis provides valuable insights into the trade-offs between system efficiency, equitable response, and performance under uncertain conditions. Based on the models, we performed sensitivity analysis across stations. We identified the bottleneck stations with non-zero shadow prices and made staffing suggestions to dispatch areas.