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Computational comparison of five maximal covering models for locating ambulances

Title	Computational comparison of five maximal covering models for locating ambulances
Author	Erkut, Erhan, Ingolfsson, A., Sim, T., Erdoğan, Güneş
Publication Date:	2009-01
Publication Place	- Wiley
Subject	Mathematical optimization, Ambulances, Uncertainty, Reaction time, Modelmaking
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	1538-4632
Record ID	f1fbaed4-a624-43eb-b345-1b0265e3e361
Library Location	Business Administration, Industrial Engineering
Date	2009-01
Sample Text	This article categorizes existing maximum coverage optimization models for locatingambulances based on whether the models incorporate uncertainty about (1) ambulanceavailability and (2) response times. Data from Edmonton, Alberta, Canada are used to test five different models, using the approximate hypercube model to compare solution quality between models. The basic maximum covering model, which ignores these two sources of uncertainty, generates solutions that perform far worse than those generated by more sophisticated models. For a specified number of ambulances, a model that incorporates both sources of uncertainty generates a configuration that covers up to 26% more of the demand than the configuration produced by the basic model.
DOI	10.1111/j.1538-4632.2009.00747.x
Cilt	41

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Computational comparison of five maximal covering models for locating ambulances

Author Erkut, Erhan, Ingolfsson, A., Sim, T., Erdoğan, Güneş

Publication Date 2009-01

Publication Place - Wiley

Subject Mathematical optimization, Ambulances, Uncertainty, Reaction time, Modelmaking

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 1538-4632

Record ID f1fbaed4-a624-43eb-b345-1b0265e3e361

Library Location Business Administration, Industrial Engineering

Date 2009-01

Sample Text This article categorizes existing maximum coverage optimization models for locatingambulances based on whether the models incorporate uncertainty about (1) ambulanceavailability and (2) response times. Data from Edmonton, Alberta, Canada are used to test five different models, using the approximate hypercube model to compare solution quality between models. The basic maximum covering model, which ignores these two sources of uncertainty, generates solutions that perform far worse than those generated by more sophisticated models. For a specified number of ambulances, a model that incorporates both sources of uncertainty generates a configuration that covers up to 26% more of the demand than the configuration produced by the basic model.

DOI 10.1111/j.1538-4632.2009.00747.x

Cilt 41