Publication:
Evaluation of electric vehicles station locations with an extended TOPSIS methodology using probabilistic linguistic term sets

dc.contributor.authorTUZKAYA, GÜLFEM
dc.contributor.authorKILIÇ, HÜSEYİN SELÇUK
dc.contributor.authorKALENDER, ZEYNEP TUĞÇE
dc.contributor.authorsDascıoglu B.G., Kalender Z.T., Tuzkaya G., Kilic H.S.
dc.date.accessioned2022-03-15T02:16:02Z
dc.date.accessioned2026-01-11T17:14:36Z
dc.date.available2022-03-15T02:16:02Z
dc.date.issued2020
dc.description.abstractIn recent years, the direct effects of climate change and global warming on natural resources attracts the attention to the environmental studies. Nowadays, one of the most important issues on eliminating the destructive environmental effects of increased population is electric vehicles. However, locating the charge stations for electric vehicles is still an important problem especially for crowded cities. Moreover, in real life applications, uncertainties may occur when preferences are expressed in other terms; it is usually difficult for a decision maker to show his/her preferences by utilizing just one linguistic expression due to the difficulty and vagueness of the real problems. In this study, location selection problem for electric vehicles charging stations is considered as a multi-criteria decision making problem and hesitation of decision makers among several possible linguistic terms are considered. For this reason, in this study, probabilistic linguistic terms sets are used to evaluate criteria of locating charging stations. The main aim of this paper is to compare the possible locations of charging stations in Istanbul which is the most crowded city of Turkey. For this purpose, 39 different alternative locations were considered and ranked by using an extended version of TOPSIS to find best locations for installing charging stations. © 2020, Springer Nature Switzerland AG.
dc.identifier.doi10.1007/978-3-030-23756-1_98
dc.identifier.isbn9783030237554
dc.identifier.issn21945357
dc.identifier.urihttps://hdl.handle.net/11424/248183
dc.language.isoeng
dc.publisherSpringer Verlag
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectCharging stations
dc.subjectElectric vehicles
dc.subjectMulti-criteria decision making
dc.subjectProbabilistic linguistic term sets
dc.subjectTOPSIS
dc.titleEvaluation of electric vehicles station locations with an extended TOPSIS methodology using probabilistic linguistic term sets
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage828
oaire.citation.startPage820
oaire.citation.titleAdvances in Intelligent Systems and Computing
oaire.citation.volume1029

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