Open AccessA hybrid optimization method for reallocation of mobile resources
Author(s) -
Jorge Catumba,
Leonar G. Aguiar,
Johan Manuel Redondo,
Rafael R Rentería,
José Octaviano Barrera
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1702/1/012013
Subject(s) - genetic algorithm , computer science , attendance , population , emergency response , event (particle physics) , response time , real time computing , operations research , mathematical optimization , medical emergency , machine learning , engineering , medicine , mathematics , physics , computer graphics (images) , environmental health , quantum mechanics , economics , economic growth
In this paper, we propose a hybrid optimization method to compute a reallocation of ambulances to obtain improved response times. As we want to minimize response times by changing ambulances allocations, we develop a hybrid algorithm based on a genetic algorithm, with randomized ambulances configurations as population individuals. Also, we embed into the genetic algorithm discrete event simulations to model the reporting, assignment, travel, and attendance processes. We later find that the algorithm optimizes the response times for simulated events, even though these times don’t yet compare to response times found in real data. So, we need to evaluate any improvement in real response times. As a study case, we use data from 2014 to 2017 provided by the health authority of Bogotá, Colombia, that contains real values of emergency medical incidents, and the quantity and type of ambulances that attended such incidents.