Electric Vehicle Selection by Using Fuzzy KEMIRA

Öztayşi B., Çevik Onar S., Kahraman C.

JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, vol.37, no.3-4, pp.437-461, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 3-4
  • Publication Date: 2021
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, zbMATH
  • Page Numbers: pp.437-461
  • Keywords: KEMIRA, fuzzy sets, electric vehicle selection, TOPSIS, EXTENSION, RANKING
  • Istanbul Technical University Affiliated: Yes


One of the most important global problems we face is global warming which affects both the environment and quality of life. Greenhouse gas (GHG) emissions are one of the most important factors of global warming, using fossil fuels for transportation and power generation increases GHG emissions and thus causes global warming. As a response, policymakers all over the world are empowering renewable and clean energy. In the transportation sector, the most effective way to decrease GHG emissions is to increase the utilization of electronic vehicles. As the manufacturers are moving towards the production of electronic vehicles both the quantity and the quality of the alternatives increase. Accordingly, the consumers face a new decision problem about the selection of electric vehicles. The electric vehicle selection problem is a multicriteria decision-making problem that includes various conflicting criteria and alternatives. The criteria considered within the scope of the problem may involve the benefit type of criteria such as design, capacity, and cost type criteria such as price, acceleration. In this study, we propose Fuzzy KEmeny Median Indicator Ranks Accordance (F-KEMIRA) as an extension of the KEMIRA method. In this study, we construct a decision model involving three benefit criteria, three cost criteria, and 5 alternatives and solve it by using the proposed Fuzzy KEMIRA method.