Prioritizing Mobility of Ambulances Based on a Bi-criterion and Multistage Approach in Overload Situations

Stamatios Vasalakis and Athanasios Spyridakos ()
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Stamatios Vasalakis: University of West Attica, Aigaleo
Athanasios Spyridakos: University of West Attica, Aigaleo

A chapter in Operational Research in the Era of Digital Transformation and Business Analytics, 2023, pp 39-47 from Springer

Abstract: Abstract This research work aims to develop a deterministic methodological approach for transportation problems of ambulances in natural disasters, where there are strong needs for immediate response and the number of cases is high. The proposed methodological approach is based on the principles of Dynamical Programming (DP), which discretizes the optimization problems in stages and the techniques of Linear Programming (LP) to identify the optimal transportation plan at every stage. In addition, the dynamic of the problem is enhanced by the usage of live data from Google. This kind of problem is considered multiplicative because there are two principal objectives (a) the emergency to transport the injured according to their triage scale and (b) the immediate movement of the patients to the hospitals. Also, the problem can be characterized as multiplicative because of (a) the existence of many start points and destination points of the ambulances with different distances and availabilities, (b) the destination points of one stage become the start points of the next stage, increasing the multiplicity of the problem and (c) the need to achieve global optimization of the time response in relation to the emergency and priorities of the patients’ condition. The above proposed methodological approach is illustrated through a case study involving the timely transfer of injured people as a result of a natural disaster to the nearest hospitals at a local level.

Keywords: Linear programming; Dynamical programming; Transportation; Risk management; Emergency treatment; Australasian triage scale (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-24294-6_5

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DOI: 10.1007/978-3-031-24294-6_5

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