Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

An Efficient Exact Hypercube Model with Fully Dedicated Servers

Full text
Author(s):
Beojone, Caio Vitor [1] ; de Souza, Regiane Maximo [1] ; Iannoni, Ana Paula [2, 3]
Total Authors: 3
Affiliation:
[1] Sao Paulo State Univ UNESP, Dept Prod Engn, BR-17033360 Bauru, SP - Brazil
[2] Ecole Cent Paris, Lab Genie Ind, F-92295 Chatenay Malabry - France
[3] Sao Carlos Fed Univ UFSCar, Dept Prod Engn, BR-13565905 Sao Carlos - Brazil
Total Affiliations: 3
Document type: Journal article
Source: TRANSPORTATION SCIENCE; v. 55, n. 1, p. 222-237, JAN-FEB 2021.
Web of Science Citations: 0
Abstract

The hypercube model is a useful descriptive tool to evaluate emergency services such as firefighters, police, and emergency medical services where geographically distributed vehicles and personnel serve users in emergencies. This study proposes an extension of the hypercube model to represent a dispatch policy in which advanced equipped servers serve solely life-threatening calls (called dedicated servers). The proposed approach is applied to two case studies of public medical emergency services in two different cities in Brazil and validated with discrete-event simulations. The computational experiments show the proposed model as more sensitive to respond to more life-threatening requests than other hypercube models in the literature, serving more of these requests under increased demand. In addition, to reduce the number of equilibrium equations and, consequently, the computational effort of the hypercube model, an aggregate model is shown based on the grouping of homogeneous servers located in the same station. The aggregation policy does not generate additional losses in the accuracy of the model, as shown through several experiments. (AU)

FAPESP's process: 15/05324-4 - Study and Modeling Problems Logistics Emergency Service
Grantee:Regiane Máximo de Souza
Support Opportunities: Regular Research Grants