The Ambulance Location and Dispatching Problem (ALDP) identifies the location of the available ambulances and the best dispatching policy to minimize the response times to answer the calls. However, the uncertain nature of the emergency calls makes it impossible to know in advance if the ambulance identified by the dispatching policy is available or not upon a call arrival. Thus, the probability that a vehicle is busy when a call arises, denoted as busy fraction, is usually considered in the literature. Probabilities can be estimated in several manners, but simulation seems to be well suited for this purpose. In this work, we propose four Recursive Optimization-Simulation Approaches to estimate the ALDP busy fraction, and we apply them to a set of realistic instances. Numerical results confirm that the most sophisticated and computing demanding approaches offer a better performance.

(2018). A recursive optimization-simulation approach for the ambulance location and dispatching problem . Retrieved from http://hdl.handle.net/10446/171352

A recursive optimization-simulation approach for the ambulance location and dispatching problem

Lanzarone, Ettore;
2018-01-01

Abstract

The Ambulance Location and Dispatching Problem (ALDP) identifies the location of the available ambulances and the best dispatching policy to minimize the response times to answer the calls. However, the uncertain nature of the emergency calls makes it impossible to know in advance if the ambulance identified by the dispatching policy is available or not upon a call arrival. Thus, the probability that a vehicle is busy when a call arises, denoted as busy fraction, is usually considered in the literature. Probabilities can be estimated in several manners, but simulation seems to be well suited for this purpose. In this work, we propose four Recursive Optimization-Simulation Approaches to estimate the ALDP busy fraction, and we apply them to a set of realistic instances. Numerical results confirm that the most sophisticated and computing demanding approaches offer a better performance.
2018
Lanzarone, Ettore; Galluccio, Enrico; Bélanger, Valerie; Nicoletta, Vittorio; Ruiz, Angel
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/171352
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