Location Selection of Electric Vehicle Charging Stations Through Employing the Spherical Fuzzy CoCoSo and CRITIC Technique

Yan, Rong; Han, Yongguang; Zhang, Huiyuan; Wei, Cun

doi:10.15388/24-INFOR545

Informatica

Location Selection of Electric Vehicle Charging Stations Through Employing the Spherical Fuzzy CoCoSo and CRITIC Technique

Volume 35, Issue 1 (2024), pp. 203–225

Rong Yan Yongguang Han Huiyuan Zhang Cun Wei

https://doi.org/10.15388/24-INFOR545

Pub. online: 8 March 2024 Type: Research Article

Open Access

Received
1 October 2022

Accepted
1 February 2024

Published
8 March 2024

Abstract

Energy conservation and emission reduction are important policies vigorously promoted in China. With the continuous popularization of the concept of green transportation, electric vehicles have become a green transportation tool with good development prospects, greatly reducing the pressure on the environment and resources caused by rapid economic growth. The development status of electric vehicles has a significant impact on urban energy security, environmental protection, and sustainable development in China. With the widespread application of new energy vehicles, charging piles have become an important auxiliary infrastructure necessary for the development of electric vehicles. They have significant social and economic benefits, so it is imperative to build electric vehicle charging piles. There are many factors to consider in the scientific layout of electric vehicle charging stations, and the location selection problem of electric vehicle charging stations is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Combined Compromise Solution (CoCoSo) technique and CRITIC technique have been utilized to deal with MAGDM issues. Spherical fuzzy sets (SFSs) can uncover the uncertainty and fuzziness in MAGDM more effectively and deeply. In this paper, on basis of CoCoSo technique, a novel spherical fuzzy number CoCoSo (SFN-CoCoSo) technique based on spherical fuzzy number cosine similarity measure (SFNCSM) and spherical fuzzy number Euclidean distance (SFNED) is conducted for dealing with MAGDM. Moreover, when the attribute weights are completely unknown, the CRITIC technique is extended to SFSs to acquire the attribute weights based on the SFNCSM and SFNED. Finally, the SFN-CoCoSo technique is utilized for location selection problem of electric vehicle charging stations to prove practicability of the developed technique and compare the SFN-CoCoSo technique with existing techniques to further demonstrate its superiority.

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Biographies

Yan Rong

R. Yan was born in Hubei in 1985, and graduated from Hainan Tropical Ocean University with a master’s degree. Now, he works as a teacher at Chongqing City Vocational College. His main research fields are tourism planning and business administration.

Han Yongguang

Y. Han was born in Shandong in 1982, graduated with a master’s degree from Chongqing Normal University and is now works as a teacher at Chongqing City Vocational College. The main research areas are scenic spot planning and project management.

Zhang Huiyuan

H. Zhang currently is a PhD student at the School of Mathematical Sciences, Sichuan Normal University, Chengdu, 610066, PR. China. She is currently interested in aggregation operators, decision making and computing with words.

Wei Cun

weicun1990@163.com

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Keywords

multiple-attribute group decision-making (MAGDM) spherical fuzzy sets (SFSs) CoCoSo technique CRITIC technique location selection

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