Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89258
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorXu, Men_US
dc.creatorMeng, Qen_US
dc.date.accessioned2021-03-02T03:55:00Z-
dc.date.available2021-03-02T03:55:00Z-
dc.identifier.issn0191-2615en_US
dc.identifier.urihttp://hdl.handle.net/10397/89258-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectCharging station locationen_US
dc.subjectBranch-and-priceen_US
dc.subjectPath deviationen_US
dc.subjectNonlinear elastic demanden_US
dc.titleOptimal deployment of charging stations considering path deviation and nonlinear elastic demanden_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage120en_US
dc.identifier.epage142en_US
dc.identifier.volume135en_US
dc.identifier.doi10.1016/j.trb.2020.03.001en_US
dcterms.abstractThis study aims to determine the optimal deployment of charging stations for battery electric vehicles (BEVs) by maximizing the covered path flows taking into account the path deviation and nonlinear elastic demand, referred to as DCSDE for short. Under the assumption that the travel demand between OD pairs follows a nonlinear inverse cost function with respect to the generalized travel cost, a BCAP-based (battery charging action-based path) model will be first formulated for DCSDE problem. A tailored branch-and-price (B&P) approach is proposed to solve the model. The pricing problem to determine an optimal path of BEV is not easily solvable by available algorithms due to the path-based nonlinear cost term in the objective function. We thus propose a customized two-phase method for the pricing problem. The model framework and solution method can easily be extended to incorporate other practical requirements in the context of e-mobility, such as the maximal allowable number of stops for charging and the asymmetric round trip. The numerical experiments in a benchmark 25-node network and a real-world California State road network are conducted to assess the efficiency of the proposed model and solution approach.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part B, Methodological, May 2020, v. 135, p. 120-142en_US
dcterms.isPartOfTransportation research. Part B, Methodologicalen_US
dcterms.issued2020-05-
dc.identifier.isiWOS:000527559500005-
dc.identifier.eissn1879-2367en_US
dc.description.validate202103 bcwhen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera0588-n04-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextRGC: 25207319; Others: P0030389; P0000250en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2022-05-31en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2022-05-31
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