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

Abstract

In 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.