Citation

Chou CC, Chiang WC, Chen AY. Transp. Res. E Logist. Transp. Rev. 2022; 158: e102591.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.tre.2021.102591

PMID

unavailable

Abstract

The response efficiency of Emergency Medical Service (EMS) is related to the survival rate of patients in Mass Casualty Incidents (MCIs). This study aims to reduce delays caused by congestions in the transportation network and also that in hospitals. A patient transportation and assignment model is proposed considering routing of ambulances and operational conditions of hospitals for an efficient MCI response. The proposed model is composed of a Cell Transmission Model (CTM) and a nonlinear treatment impedance function. A Lagrangian heuristic is utilized to expedite model solution by decomposing the problem into two relatively tractable sub-problems: one linear and the other nonlinear. The linear sub-problem is solved by the simplex algorithm, and is related to ambulance routing, while the nonlinear sub-problem is solved by a gradient projection algorithm for the optimization of patients' hospital assignment. A case study and several benchmark networks were tested, and the proposed methodology outperformed a typical Lagrangian Relaxation approach. This work has the potential to enable a more efficient patient assignment in MCIs.

Language: en

Keywords

Cell transmission model; Emergency medical service; Gradient projection; Hospital delay; Lagrangian relaxation; Mass casualty incident