We propose the development and application of a multi-objective biased random-key genetic algorithm to identify sets of ambulance locations in a rural-mountainous area. The algorithm involves a discrete event simulator to estimate the objective functions, thus we want to minimize the response time while maximizing the area served within the standard time. It is applied to the case of the mountainous area of the Italian region of Friuli Venezia Giulia. Preliminary results are encouraging, as the best case for each objective shows that the average response time decreases of 28.9%, the 90th percentile for the response time decreases of 43.0%, the number of municipalities served within the standard time increases of 8 units during the day, and of 26 units during the night.
A Multi-objective Biased Random-Key Genetic Algorithm for the Siting of Emergency Vehicles
Da Ros F.;Di Gaspero L.;La Barbera D.;Della Mea V.;Roitero K.;Deroma L.;Licata S.;
2023-01-01
Abstract
We propose the development and application of a multi-objective biased random-key genetic algorithm to identify sets of ambulance locations in a rural-mountainous area. The algorithm involves a discrete event simulator to estimate the objective functions, thus we want to minimize the response time while maximizing the area served within the standard time. It is applied to the case of the mountainous area of the Italian region of Friuli Venezia Giulia. Preliminary results are encouraging, as the best case for each objective shows that the average response time decreases of 28.9%, the 90th percentile for the response time decreases of 43.0%, the number of municipalities served within the standard time increases of 8 units during the day, and of 26 units during the night.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
