A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network

Geroliminis, N; Kepaptsoglou, K; Karlaftis, MG

dc.contributor.author	Geroliminis, N	en
dc.contributor.author	Kepaptsoglou, K	en
dc.contributor.author	Karlaftis, MG	en
dc.date.accessioned	2014-03-01T01:34:53Z
dc.date.available	2014-03-01T01:34:53Z
dc.date.issued	2011	en
dc.identifier.issn	0377-2217	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20922
dc.subject	Emergency response	en
dc.subject	Genetic algorithms	en
dc.subject	Hypercube	en
dc.subject	Spatial queues	en
dc.subject.classification	Management	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Approximate solution	en
dc.subject.other	Athens , Greece	en
dc.subject.other	Emergency response	en
dc.subject.other	Genetic algorithm approach	en
dc.subject.other	Heuristic solutions	en
dc.subject.other	Hypercube	en
dc.subject.other	Hypercube model	en
dc.subject.other	Location models	en
dc.subject.other	Metaheuristic optimization	en
dc.subject.other	Mobile units	en
dc.subject.other	Optimal deployment	en
dc.subject.other	Queuing models	en
dc.subject.other	Service area	en
dc.subject.other	Spatial queues	en
dc.subject.other	Stochastic nature	en
dc.subject.other	Sub-areas	en
dc.subject.other	Two-step approach	en
dc.subject.other	Urban networks	en
dc.subject.other	Urban transportation networks	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Geometry	en
dc.subject.other	Optimization	en
dc.subject.other	Queueing theory	en
dc.subject.other	Transportation routes	en
dc.subject.other	Wireless networks	en
dc.subject.other	Stochastic models	en
dc.title	A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ejor.2010.08.031	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ejor.2010.08.031	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	Emergency response services are critical for modern societies. This paper presents a model and a heuristic solution for the optimal deployment of many emergency response units in an urban transportation network and an application for transit mobile repair units (TMRU) in the city of Athens, Greece. The model considers the stochastic nature of such services, suggesting that a unit may be already engaged, when an incident occurs. The proposed model integrates a queuing model (the hypercube model), a location model and a metaheuristic optimization algorithm (genetic algorithm) for obtaining appropriate unit locations in a two-step approach. In the first step, the service area is partitioned into sub-areas (called superdistricts) while, in parallel, necessary number of units is determined for each superdistrict. An approximate solution to the symmetric hypercube model with spatially homogeneous demand is developed. A Genetic Algorithm is combined with the approximate hypercube model for obtaining best superdistricts and associated unit numbers. With both of the above requirements defined in step one, the second step proceeds in the optimal deployment of units within each superdistrict. (C) 2010 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	European Journal of Operational Research	en
dc.identifier.doi	10.1016/j.ejor.2010.08.031	en
dc.identifier.isi	ISI:000286853300017	en
dc.identifier.volume	210	en
dc.identifier.issue	2	en
dc.identifier.spage	287	en
dc.identifier.epage	300	en