ORAHS2025
Abstract Submission

40. A multiperiod resource minimization model for rural emergency medical services networks with ground and air ambulances

Invited abstract in session HD-4: Poster session 2, stream Sessions.

Thursday, 13:30-14:00
Room: St Olavs, Kunnskapssenteret KA12

Authors (first author is the speaker)

1. Lieke Jansen
Operations, University of Groningen
2. Iris F.A. Vis
Faculty of Economics and Business, Dep. of Operations, University of Groningen
3. Ilke Bakir
Department of Operations, University of Groningen
4. Durk-Jouke van der Zee
Operations, University of Groningen

Abstract

Emergency Medical Services (EMS) must meet strict response time standards to ensure timely care for life-threatening emergencies. However, achieving these standards in rural areas is challenging due to long travel distances, low call volumes, and staff shortages. Since increasing the number of ambulances is usually not feasible in rural EMS systems, they could benefit from replacing some of their ground ambulances with air ambulances with a large range to enhance coverage. We propose a model that optimizes the number and locations of ground and air ambulances across different shifts while ensuring response time compliance. Unlike traditional EMS optimization approaches, our model evaluates system-wide response time compliance rather than individual demand-node performance. The problem is formulated as a mixed-integer nonlinear programming (MINLP) model incorporating nonlinearities in the coverage computation. Given the complexity of large-scale instances, we develop an adaptive large neighborhood search (ALNS) metaheuristic. Additionally, we introduce an approximation method to assign calls to vehicles and estimate busy probabilities, including less urgent calls. Our approach is validated using real-world EMS data from the Dutch Province of Friesland, incorporating electric vertical take-off and landing (eVTOL) aircraft as air ambulances. Results show that integrating air ambulances as rapid response units enhances coverage while minimizing resource use.

Keywords

Status: accepted


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