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Range coverage location model: An optimization model for the charging station location problem in a transportation network to cover intercity travels

dc.contributor.authorYılmaz Hilal
dc.contributor.authorYağmahan, Betül
dc.contributor.buuauthorYılmaz Hilal
dc.contributor.buuauthorYAĞMAHAN, BETÜL
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentEndüstri Mühendisliği Bölümü
dc.contributor.orcid0000-0003-1744-3062
dc.contributor.orcid0000-0001-8125-6814
dc.contributor.researcheridGZG-5051-2022
dc.contributor.researcheridB-5557-2017
dc.date.accessioned2024-06-25T06:52:05Z
dc.date.available2024-06-25T06:52:05Z
dc.date.issued2021-09-14
dc.description.abstractEquipping highways with charging stations (CSs) is a fundamental step for travelling with electric vehicles (EVs) between cities and countries conveniently. This article focuses on locating CSs to fully connect roads that may require multiple charging events by considering the minimum driving range for all possible paths in a transportation network. For this purpose, we present a new binary integer linear programming model named the Range Coverage Location Model (RCLM) to find the minimum required CSs and their locations that the driving range can cover without defining the paths in the network. By adding the result of RCLM as a constraint to the model, the optimum locations that maximize the EV flows are determined with the RCLM-Max model. Two versions of the RCLM are introduced. The link-based RCLM is designed for problems in which there are CSs in each of the origin/destination (OD) nodes (intersections), while the network-based RCLM aims to connect links without stopping by the OD nodes, making the model stricter but convenient for EV travels. The proposed models are validated through extensive computational experiments with real data from a highway network in Turkey. The experiments show that RCLM and RCLM-Max can solve very large-scale problems in a very short CPU time. The findings suggest that the link-based RCLM can be applied when the budget is at the forefront, and the network-based model is preferred if the aim is to connect the main roads without stopping by the OD nodes.
dc.identifier.doi10.1002/er.7268
dc.identifier.eissn1099-114X
dc.identifier.endpage1552
dc.identifier.issn0363-907X
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85114765361
dc.identifier.startpage1538
dc.identifier.urihttps://doi.org/10.1002/er.7268
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1002/er.7268
dc.identifier.urihttps://hdl.handle.net/11452/42330
dc.identifier.volume46
dc.identifier.wos000695911500001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherWiley
dc.relation.journalInternational Journal of Energy Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectElectric vehicles
dc.subjectInfrastructure
dc.subjectFormulation
dc.subjectCharging station location problem
dc.subjectDriving range
dc.subjectElectric vehicles
dc.subjectHighway network
dc.subjectInteger linear programming
dc.subjectScience & technology
dc.subjectTechnology
dc.subjectEnergy & fuels
dc.subjectNuclear science & technology
dc.titleRange coverage location model: An optimization model for the charging station location problem in a transportation network to cover intercity travels
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Endüstri Mühendisliği Bölümü
local.indexed.atWOS
local.indexed.atScopus
relation.isAuthorOfPublication73b94a30-324b-44e7-8d61-14cd859da4c3
relation.isAuthorOfPublication.latestForDiscovery73b94a30-324b-44e7-8d61-14cd859da4c3

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