Optimizing the location-allocation problem of bike sharing stations: A case study in gaziantep university campus

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A growing number of cities are implementing bike-sharing programs to increase bicycle use. One of the key factors for the success of such programs is the location of bike stations in relation to potential demand. In this paper, potential locations of bike sharing stations in Gaziantep University campus are investigated to provide optimal utilization for users. To do so, first of all, 20 demand points and 20 potential bike stations are determined. Second, set covering mathematical model is handled to determine coverage capability of potential bike stations. Finally, P-center and P-median mathematical models are applied to set up potential stations and to assign demand points to the opened stations so that the total walking distance can be minimized. Computational experiments prove that our approach can find new potential bike stations which cover all demand points.

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dc.contributor.authorÖzceylan, Eren
dc.contributor.authorMete, Süleyman
dc.contributor.authorÇil, Zeynel Abidin
dc.contributor.editorDrobne, S.
dc.contributor.editorZerovnik, J.
dc.contributor.editorZadnik Stirn, L.
dc.contributor.editorKljajic Borstar, M.
dc.date.accessioned2026-10-28T14:57:13.442519012Z
dc.date.available2026-10-28T14:57:13.442519012Z
dc.date.issued2017
dc.description.abstractA growing number of cities are implementing bike-sharing programs to increase bicycle use. One of the key factors for the success of such programs is the location of bike stations in relation to potential demand. In this paper, potential locations of bike sharing stations in Gaziantep University campus are investigated to provide optimal utilization for users. To do so, first of all, 20 demand points and 20 potential bike stations are determined. Second, set covering mathematical model is handled to determine coverage capability of potential bike stations. Finally, P-center and P-median mathematical models are applied to set up potential stations and to assign demand points to the opened stations so that the total walking distance can be minimized. Computational experiments prove that our approach can find new potential bike stations which cover all demand points.
dc.identifier.endpage146
dc.identifier.isbn978-961616550-1
dc.identifier.scopus2-s2.0-85051730011
dc.identifier.startpage141
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/3857
dc.identifier.volume2017-September
dc.language.isoen
dc.publisherSLOVENIAN SOCIETY INFORMATIKA
dc.relation.conference14th International Symposium on Operational Research, SOR 2017
dc.relation.ispartofProceedings of the 14th International Symposium on Operational Research, SOR 2017
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBike sharing station
dc.subjectGaziantep
dc.subjectInteger programming
dc.subjectLocation-allocation models
dc.subject.otherInteger programming
dc.subject.otherLocation
dc.subject.otherBike sharing station
dc.subject.otherComputational experiment
dc.subject.otherGaziantep
dc.subject.otherLocation allocation problem
dc.subject.otherLocation-allocation models
dc.subject.otherOptimal utilization
dc.subject.otherPotential demand
dc.subject.otherUniversity campus
dc.subject.otherBicycles
dc.titleOptimizing the location-allocation problem of bike sharing stations: A case study in gaziantep university campus
dc.typeConference Object
rdl.citation.scopus5
rdl.conference.date27 September 2017 through 29 September 2017
rdl.conference.placeBled
rdl.oa.statusclosed
rdl.source.indexSCOPUS