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

BİLSEL M., KILIÇ H. S., KALENDER Z. T., TUZKAYA G.

Computers and Industrial Engineering, cilt.198, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 198
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.cie.2024.110695
  • Dergi Adı: Computers and Industrial Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: AUGMECON2, Capacity allocation, Electric vehicle charging stations, Location selection, Mathematical modeling, Multi-objective optimization
  • Marmara Üniversitesi Adresli: Evet

Özet

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.