The University of Southampton
University of Southampton Institutional Repository

Scheduling ambulance crews for maximum coverage

Scheduling ambulance crews for maximum coverage
Scheduling ambulance crews for maximum coverage
This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for this subproblem. Two integer programming models that use the output of the tabu search algorithm are constructed for the main problem. Computational experiments with real data are conducted. A comparison of the results of the models is presented.
0160-5682
543-550
Erdogan, Gunes
468310a1-5c36-4c3d-8b39-079bd621b34b
Erkut, Erhan
756888bd-dd7a-485e-a68c-384760276af4
Ingolfsson, Armann
238232b8-75d6-49da-b39c-70c8d0c7238a
Laporte, Gilbert
b8210b8f-e942-4c5c-98b1-b55bd916aa70
Erdogan, Gunes
468310a1-5c36-4c3d-8b39-079bd621b34b
Erkut, Erhan
756888bd-dd7a-485e-a68c-384760276af4
Ingolfsson, Armann
238232b8-75d6-49da-b39c-70c8d0c7238a
Laporte, Gilbert
b8210b8f-e942-4c5c-98b1-b55bd916aa70

Erdogan, Gunes, Erkut, Erhan, Ingolfsson, Armann and Laporte, Gilbert (2010) Scheduling ambulance crews for maximum coverage. Journal of the Operational Research Society, 61, 543-550. (doi:10.1057/jors.2008.163).

Record type: Article

Abstract

This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for this subproblem. Two integer programming models that use the output of the tabu search algorithm are constructed for the main problem. Computational experiments with real data are conducted. A comparison of the results of the models is presented.

This record has no associated files available for download.

More information

Published date: April 2010
Organisations: Centre of Excellence for International Banking, Finance & Accounting

Identifiers

Local EPrints ID: 204817
URI: http://eprints.soton.ac.uk/id/eprint/204817
ISSN: 0160-5682
PURE UUID: 92e957b6-2765-4592-b84d-3fd0cfc6e807

Catalogue record

Date deposited: 01 Dec 2011 15:47
Last modified: 14 Mar 2024 04:32

Export record

Altmetrics

Contributors

Author: Gunes Erdogan
Author: Erhan Erkut
Author: Armann Ingolfsson
Author: Gilbert Laporte

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×