Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach
Publication Date
2018Journal Title
Mathematical Problems in Engineering
ISSN
1024-123X
Publisher
Hindawi Limited
Type
Journal Article
Metadata
Show full item recordCitation
Cui, F., You, X., Shi, H., & Liu, H. (2018). Optimal Siting of Electric Vehicle Charging Stations Using Pythagorean Fuzzy VIKOR Approach. [Journal Article]. https://doi.org/10.1155/2018/9262067
Abstract
<jats:p>Site selection for electric vehicle charging stations (EVCSs) is the process of determining the most suitable location among alternatives for the construction of charging facilities for electric vehicles. It can be regarded as a complex multicriteria decision-making (MCDM) problem requiring consideration of multiple conflicting criteria. In the real world, it is often hard or impossible for decision makers to estimate their preferences with exact numerical values. Therefore, Pythagorean fuzzy set theory has been frequently used to handle imprecise data and vague expressions in practical decision-making problems. In this paper, a Pythagorean fuzzy VIKOR (PF-VIKOR) approach is developed for solving the EVCS site selection problems, in which the evaluations of alternatives are given as linguistic terms characterized by Pythagorean fuzzy values (PFVs). Particularly, the generalized Pythagorean fuzzy ordered weighted standardized distance (GPFOWSD) operator is proposed to calculate the utility and regret measures for ranking alternative sites. Finally, a practical example in Shanghai, China, is included to demonstrate the proposed EVCS sitting model, and the advantages are highlighted by comparing the results with other relevant methods.</jats:p>
Keywords
7 Affordable and Clean Energy
Identifiers
External DOI: https://doi.org/10.1155/2018/9262067
This record's DOI: https://doi.org/10.17863/CAM.25016
Rights
Rights Holder: Copyright © 2018 Feng-Bao Cui et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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