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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 9/2020

28.09.2018 | Original Article

Location selection of electric vehicles charging stations by using a fuzzy MCDM method: a case study in Turkey

verfasst von: Ali Karaşan, İhsan Kaya, Melike Erdoğan

Erschienen in: Neural Computing and Applications | Ausgabe 9/2020

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Abstract

Pollution, climate change, fast natural resource depletion, deforestation and global warming have become major worldwide problems relevant with the petroleum-based powered vehicles and alternatives for this conventional transportation type have been started to change in the last decade. In this modification process, electric vehicles (EVs) have a leading position due to their low damage effect to the environment. Selecting the most sustainable location for charging station for EVs plays an important role in the life cycle of them. This process needs to consider some conflicting criteria and has a complex decision problem that can be modeled as a multi-criteria decision-making problem. The inclusion of such criteria in a location selection requires the fuzzy sets to be used in the decision-making methodology. For this aim, intuitionistic fuzzy sets have been used in this paper. By the way, a decision-making procedure based on intuitionistic fuzzy sets and consists of the decision-making trial and evaluation laboratory, analytic hierarchy process and technique for order preference by similarity to ideal solution has been suggested for the location selection of charge stations. The proposed fuzzy-based model is applied to a case study for Istanbul in Turkey.
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Metadaten
Titel
Location selection of electric vehicles charging stations by using a fuzzy MCDM method: a case study in Turkey
verfasst von
Ali Karaşan
İhsan Kaya
Melike Erdoğan
Publikationsdatum
28.09.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3752-2

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