Comparative analysis of relocation strategies for ambulances in the city of Tijuana, Mexico

Abstract

This paper analyzes the problem of locating ambulances for the Red Cross of Tijuana, Baja California, Mexico, considering demand changes over time, a problem that usually requires relocating ambulances at specific moments in time. This problem is usually solved using optimization models, seeking to maximize coverage and reduce the response time using an appropriate relocation strategy, while also minimizing the cost of relocating ambulances across the city. The goal of this work is to determine the benefits and costs, advantages and disadvantages, of using different strategies to solve this problem for the Red Cross of Tijuana. Therefore, different solution strategies are evaluated, all of them are based on the Double Standard Model (DSM) for ambulance locations. The first approach is to apply a robust version of the DSM, Robust DSM, that finds the best trade-off solutions across all possible time periods, or scenarios, throughout the day. The second approach is to apply the DSM to each scenario independently, and then perform relocations based on the different configurations of the ambulances in different scenarios. The final approach is to use an explicit relocation model, the multi-period DSM. The approaches are evaluated based on the percentage of double coverage, total number of relocations, relocation travel time, relocation travel distance and the financial cost of performing relocations. More than 13,000 calls for Emergency Medical Services (EMS) were analyzed, received by the Red Cross from August 2016 to April 2017, such that the results obtained are based on a comprehensive characterization of this real-world case study. Results show that while the relocation approaches do provide better overall coverage, for the Red Cross of Tijuana, an EMS provider with limited resources and funding, the increased coverage may not justify the additional costs.

Keywords: Ambulances; Double coverage models; Emergency medical services; Red Cross; Relocation problem; Travel cost.