Computational Comparison of Five Maximal Covering Models for Locating Ambulances

University of Alberta School of Business Research Paper 2013-189

Geographical Analysis, Vol. 41, Issue 1, 2008

Posted: 28 Jun 2013

See all articles by Erhan Erkut

Erhan Erkut

Independent

Armann Ingolfsson

University of Alberta - Department of Accounting, Operations & Information Systems

Thaddeus Sim

Independent

Güneş Erdoğan

School of Management, University of Southampton

Date Written: January 1, 2008

Abstract

This article categorizes existing maximum coverage optimization models for locating ambulances based on whether the models incorporate uncertainty about (1) ambulance availability 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.

Suggested Citation

Erkut, Erhan and Ingolfsson, Armann and Sim, Thaddeus and Erdogan, Gunes, Computational Comparison of Five Maximal Covering Models for Locating Ambulances (January 1, 2008). University of Alberta School of Business Research Paper 2013-189, Geographical Analysis, Vol. 41, Issue 1, 2008, Available at SSRN: https://ssrn.com/abstract=2274929

Armann Ingolfsson

University of Alberta - Department of Accounting, Operations & Information Systems ( email )

Edmonton, Alberta T6G 2R6
Canada

Thaddeus Sim

Independent ( email )

Gunes Erdogan

School of Management, University of Southampton ( email )

Highfield
Southampton S017 1BJ, Hampshire SO17 1BJ
United Kingdom

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