Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS. Issue 2 (2nd April 2020)

• Record Type: Journal Article
• Authors: Guler, Dogus; Yomralioglu, Tahsin
• Is Part Of: Annals of GIS. Volume 26:Issue 2(2020)
• Page Start: 169
• Page End: 189
• Publication Date: 2020-04-02
• Subjects: Geographic Information Systems (GIS) -- Multi-Criteria Decision Making (MCDM) -- Analytic Hierarchy Process (AHP) -- Fuzzy Analytic Hierarchy Process (FAHP) -- electric vehicle charging station -- location selection; Geographic information systems -- Periodicals; Periodicals; 910.285
• DOI: 10.1080/19475683.2020.1737226
• Languages: English
• ISSNs: 1947-5683

Abstract

ABSTRACT: Electric vehicles arouse interest since they not only contribute economies of countries in the context of dependency to oil but also support to more livable and sustainable urban areas. The location selection of electric vehicle charging stations is one of the most vital topics in order to enhance the use of electric vehicles. In this sense, the aim of this paper is to propose an approach that integrates Geographic Information System (GIS) techniques and Multi-Criteria Decision Making (MCDM) methods for finding suitable locations of the electric vehicle charging stations. In this regard, the Analytic Hierarchy Process (AHP) and the Fuzzy Analytic Hierarchy Process (FAHP) methods are used to calculate the weights of criteria. While the two different weights for each criterion are obtained by means of AHP in terms of environmental impact and accessibility, another weight for each criterion is obtained as a means of applying the FAHP. The intersection of three different suitability indexes is determined so as to achieve a holistic, credible result. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the alternative locations. The results show that the proposed approach offers a notable solution to be selected suitable charging station locations. Moreover, policymakers and administrators could benefit from these results in order to make efficient decisions for forward planning and strategies.