Stochastic travel times for ambulance optimal (re)location-allocation

I. Gago Carro, M. Merino Maestre, U. Aldasoro Marcellan, D. Lee

The precision of the response given to health emergencies is imperative. A rapid response can mean the difference between a patient's life and death in serious situations. For the efficiency of emergency services, the location of ambulances is crucial, as is the allocation of ambulances to emergencies. This work approaches the ambulance location-allocation problem in the geographical area of the Basque Country. A two-stage stochastic 0-1 integer linear programming model is presented to that end.

Considering deterministic ambulance travel times can lead to an oversimplified representation of ambulance management. Thus, we consider several methods to estimate ambulance travel times to obtain realistic solutions. Moreover, as the objectives to be pursued are numerous, we consider two alternative objective functions: (1) to maximize the number of emergencies responded to in target time and (2) to minimize the worst response times using a Conditional value-at-risk approach.

Keywords: Stochastic programming, Forecasting travel times, Uncertainty, OR in health services; CVaR

GT17.SDDS3 Invited Session
November 10, 2023  12:00 PM
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