Strategic fire and rescue service decision making using evolutionary algorithms

Clarke, Alastair ORCID: https://orcid.org/0000-0002-3603-6000 and Miles, John Christopher 2012. Strategic fire and rescue service decision making using evolutionary algorithms. Advances in Engineering Software 50 , pp. 29-36. 10.1016/j.advengsoft.2012.04.002

Preview

PDF Download (501kB) | Preview

Abstract

This paper describes the development of a novel, risk based method to locate high performance solutions for the deployment of Fire and Rescue Service (FRS) resources, such as fire stations and appliances, using evolutionary algorithms in conjunction with Fire Service Cover Models. Such algorithms allow the relatively rapid identification of areas of good potential solutions by sampling only a small percentage of the total search space. A real example of the use of the software to optimise vehicle locations is presented which identifies significant potential increase in efficiency and effectiveness over the existing vehicle locations.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Subjects:	T Technology > T Technology (General)
Uncontrolled Keywords:	Evolutionary algorithms; Optimisation; Decision making; Fire; Emergency services; Genetic algorithms
Publisher:	Elsevier
ISSN:	0965-9978
Last Modified:	10 May 2023 22:52
URI:	https://orca.cardiff.ac.uk/id/eprint/38671

Citation Data

Cited 10 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item