Multi-objective model for electric vehicle charging station location selection problem for a sustainable transportation infrastructure

• Published in: Computers & industrial engineering 2024-12, Vol.198, p.110695, Article 110695
• Main Authors: Bilsel, Murat, Kilic, Huseyin Selcuk, Kalender, Zeynep Tugce, Tuzkaya, Gulfem
• Format: Article
• Language: English
• Subjects: AUGMECON2; Capacity allocation; Electric vehicle charging stations; Location selection; Mathematical modeling; Multi-objective optimization
• ISSN: 0360-8352
• DOI: 10.1016/j.cie.2024.110695

•A multi-objective model is proposed for the electric vehicle charging station location problem.•Maximizing customer satisfaction, minimizing total risk and costs are considered as objective functions.•AUGMECON2, an improved version of the epsilon constraint method, is applied to find the Pareto set.•The European side of Istanbul is considered as the application area. The transportation industry mostly depends on conventional vehicles, leading to significant adverse effects on the environment. The widespread usage of electric vehicles can be seen as a relief for this problem. However, the success of electric vehicles largely depends on the availability and proper deployment of charging station infrastructure. It is crucial for cities to strategically select suitable locations for charging stations with adequate capacity levels to promote sustainable and environmentally-friendly transportation options. Hence, in this study, a multi-objective model is proposed for the electric vehicle charging station location selection and capacity allocation problem. The model aims to maximize customer satisfaction, minimize total risk, and minimize costs as key objective functions. To manage the demand effectively, the region of interest is divided into grids. The proposed multi-objective model is applied to the European side of Istanbul and solved by using AUGMECON2 technique. Finally, computational analyses are presented based on scenarios including different demand values. These analyses provide valuable insights into the effectiveness of the proposed model and its implications for achieving sustainable transportation in Istanbul.