Electric vehicles (EVs) play a vital role in reducing greenhouse gas emissions resulting in a reduction of the problem of global warming. Many of the countries are towards the deployment of electric vehicles contributing to sustainable development. Despite the rapid expansion of electric vehicles worldwide, the selection of the best alternative among available variants of EVs is difficult. This paper aims to present an integrated approach of the analytic hierarchy process (AHP) and multi-attributive border approximation area comparison (MABAC) method as a multi-criterion decision-making tool (MCDM) for the selection and ranking of the best alternative of the electric vehicle. The AHP method is used to obtain weight coefficients of criteria, and the selection of EVs alternatives is evaluated using the MABAC method. For the study, a sample of six feasible alternatives has been considered. The novelty of this work lies in the combined approach of AHP-MABAC, which has not been applied previously in this domain. This study contributes by providing a real preference for a comprehensive set of selection criteria and assessing the best alternative from available electric vehicles.

电动汽车 (EV) 在减少温室气体排放方面发挥着至关重要的作用，从而减少全球变暖问题。许多国家都在部署有助于可持续发展的电动汽车。尽管电动汽车在全球范围内迅速扩张，但很难在现有的电动汽车变体中选择最佳替代品。本文旨在提出一种将层次分析法 (AHP) 和多属性边界近似区域比较 (MABAC) 方法作为多准则决策工具 (MCDM) 的综合方法，用于选择和排名最佳替代方案。电动汽车。采用层次分析法获得准则的权重系数，采用 MABAC 方法评价电动汽车替代品的选择。为了研究，已经考虑了六个可行替代方案的样本。这项工作的新颖之处在于 AHP-MABAC 的组合方法，该方法以前尚未应用于该领域。这项研究通过提供对一套综合选择标准的真正偏好并评估可用电动汽车的最佳替代方案而有所贡献。