Genetic algorithm-based approach for optimal location of transit repair vehicles on a large urban network

Karlaftis, M; Kepaptsoglou, K; Stathopoulos, A; Jha, MK; Lovell, DJ; Kim, E

dc.contributor.author	Karlaftis, M	en
dc.contributor.author	Kepaptsoglou, K	en
dc.contributor.author	Stathopoulos, A	en
dc.contributor.author	Jha, MK	en
dc.contributor.author	Lovell, DJ	en
dc.contributor.author	Kim, E	en
dc.date.accessioned	2014-03-01T02:42:47Z
dc.date.available	2014-03-01T02:42:47Z
dc.date.issued	2004	en
dc.identifier.issn	03611981	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31080
dc.subject	Genetic Algorithm	en
dc.subject	Optimal Location	en
dc.subject.other	Level of service (LOS)	en
dc.subject.other	Private vehicles	en
dc.subject.other	Transit repair vehicles	en
dc.subject.other	Urban networks	en
dc.subject.other	Data processing	en
dc.subject.other	Decision support systems	en
dc.subject.other	Geographic information systems	en
dc.subject.other	Graphical user interfaces	en
dc.subject.other	Highway traffic control	en
dc.subject.other	Intelligent vehicle highway systems	en
dc.subject.other	Optimization	en
dc.subject.other	Real time systems	en
dc.subject.other	Repair	en
dc.subject.other	Scheduling	en
dc.subject.other	Urban planning	en
dc.subject.other	Vehicles	en
dc.subject.other	Genetic algorithms	en
dc.title	Genetic algorithm-based approach for optimal location of transit repair vehicles on a large urban network	en
heal.type	conferenceItem	en
heal.identifier.primary	10.3141/1879-06	en
heal.identifier.secondary	http://dx.doi.org/10.3141/1879-06	en
heal.publicationDate	2004	en
heal.abstract	Determining the optimal location of a fleet of vehicles is necessary in a number of potential applications, such as special repair vehicles for buses on a large public transportation network. The Athens Urban Transport Authority operates a large bus fleet over an extensive network for 19 h a day and serves a population of approximately 4 million people, all in a heavily congested road network. During the 2004 Summer Olympic Games, held in Athens, most spectators, employees, and volunteers were transported to and from Olympic Games venues by public transportation. Dedicated Olympic Games bus lines operated under a tight around-the-clock schedule. During normal operations and particularly during events such as the Olympic Games, incidents such as vehicle breakdowns and minor accidents can have a severe effect on the operation of the public transport network and can cause a significant decrease in the level of service. To help the authority locate bus repair vehicles over the entire network, a decision support system was developed on the basis of an embedded genetic algorithm used for obtaining optimal location solutions. The system's design and performance make it easy to operate under real-time conditions, which is useful for planning and for fast vehicle redeployment.	en
heal.journalName	Transportation Research Record	en
dc.identifier.doi	10.3141/1879-06	en
dc.identifier.issue	1879	en
dc.identifier.spage	41	en
dc.identifier.epage	50	en