Citation

Asgharizadeh E, Kadivar M, Noroozi M, Mottaghi V, Mohammadi H, Chobar AP. Comput. Intell. Neurosci. 2022; 2022: e2340856.

Copyright

(Copyright © 2022, Hindawi Publishing)

DOI

10.1155/2022/2340856

PMID

35845873

PMCID

PMC9283018

Abstract

In the present study, the optimization of medical services considering the role of intelligent traffic management is of concern. In this regard, a two-objective mathematical model of a medical emergency system is assessed in order to determine the location of emergency stations and determine the required number of ambulances to be allocated to the station. The objective functions are the maximization of covering the emergency demands and minimization of total costs. Moreover, the use of an intelligent traffic management system to speed up the ambulance is addressed. In this regard, the proposed two-objective mathematical model has been formulated, and a robust counterpart formulation under uncertainty is applied. In the proposed method, the values of the objective function increase as the problem becomes wider and, with a slight difference in large dimensions, converge in terms of the solution. The numerical results indicate that, as the problem's complexity increases, the robust optimization method is still effective because, with the increasing complexity of the problem, it can still solve large-scale problems in a reasonable time. Moreover, the difference between the value of the objective function in the proposed method and the presence of uncertainty parameters is very small and, in large dimensions, is quite logical and negligible. The sensitivity analysis shows that, with increasing demand, both the number of ambulances required and the amount of objective function have increased significantly.

Language: en

Keywords

*Ambulances; *Emergency Medical Services/methods; Intelligence; Models, Theoretical