Optimizing pricing policies in Park-and-Ride facilities: A model and decision support system with application

Kepaptsoglou, K; Karlaftis, MG; Li, Z-Z

dc.contributor.author	Kepaptsoglou, K	en
dc.contributor.author	Karlaftis, MG	en
dc.contributor.author	Li, Z-Z	en
dc.date.accessioned	2014-03-01T01:34:02Z
dc.date.available	2014-03-01T01:34:02Z
dc.date.issued	2010	en
dc.identifier.issn	10096744	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20660
dc.subject	Decision support system	en
dc.subject	Genetic algorithm	en
dc.subject	Optimization	en
dc.subject	Park-and-ride	en
dc.subject	Pricing policy	en
dc.subject	Pricing scheme	en
dc.subject	Shared use	en
dc.subject	Urban traffic	en
dc.title	Optimizing pricing policies in Park-and-Ride facilities: A model and decision support system with application	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S1570-6672(09)60063-5	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S1570-6672(09)60063-5	en
heal.publicationDate	2010	en
heal.abstract	Park-and-ride facilities are of major importance to the attractiveness and operation of modern transit systems because travelers tend to prefer public transportation when they are able to combine the use of these facilities with their private vehicles. Among those elements examined when developing/operating a park-and-ride facility is the pricing policy to be established for its users. Indeed, the pricing policy is among those tools that can aid transportation agencies in managing park-and-ride facilities, by providing incentives or disincentives of parking for various categories of users. This paper contributes to the literature by offering a new approach for obtaining optimal pricing schemes for a parking facility, with respect to its financial viability. In particular, a financial analysis model is combined with a genetic algorithm for determining the optimal pricing parameters for park-and-ride facilities. The model is applied for a shared-use, park-and-ride facility of the Athens metro network in Greece. Results of the computational study indicate that the model can offer near optimal pricing schemes in a short amount of time. A decision support system is also developed for incorporating the model in a user friendly computerized framework.	en
heal.journalName	Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology	en
dc.identifier.doi	10.1016/S1570-6672(09)60063-5	en
dc.identifier.volume	10	en
dc.identifier.issue	5	en
dc.identifier.spage	53	en
dc.identifier.epage	65	en