A Hybrid Intuitionistic Fuzzy-MEREC-RS-DNMA Method for Assessing the Alternative Fuel Vehicles with Sustainability Perspectives

Ibrahim M. Hezam, Arunodaya Raj Mishra, Pratibha Rani, Fausto Cavallaro, Abhijit Saha, Jabir Ali, Wadim Strielkowski and Dalia Štreimikienė
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Ibrahim M. Hezam: Statistics & Operations Research Department, College of Sciences, King Saud University, Riyadh 11451, Saudi Arabia
Arunodaya Raj Mishra: Department of Mathematics, Government College Raigaon, Satna 485441, India
Pratibha Rani: Department of Mathematics, Rajiv Gandhi National Institute of Youth Development, Sriperumbudur 602105, India
Fausto Cavallaro: Department of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy
Abhijit Saha: Department of Mathematics, Techno College of Engineering Agartala, Agartala 799004, India
Jabir Ali: Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Ghaziabad 201204, India
Dalia Štreimikienė: Institute of Social Sciences and Applied Informatics, Kaunas Faculty, Vilnius University, Muitines 8, 444280 Kaunas, Lithuania

Sustainability, 2022, vol. 14, issue 9, 1-32

Abstract: Alternative fuel vehicles (AFVs) offer opportunities to lower fuel costs as well as to reduce greenhouse gas emissions, and, therefore, they are a feasible option for customers in the market. Due to technological advancements, decisions about suitable alternative fuel vehicles are a challenging problem for fleet operators. This paper aims to introduce a multi-attribute decision-analysis framework to rank and select the “alternative fuel vehicles (AFVs)” for a private home healthcare service provider in Chandigarh, India. The selection of AFVs can be treated as a decision-making problem, because of the presence of various qualitative and quantitative attributes. Thus, the current work introduces an integrated decision-making framework based on intuitionistic fuzzy-“method based on the removal effects of criteria (MEREC)”, “ranking sum (RS)”, and the “double normalization-based multi-aggregation (DNMA)” framework for assessing the AFVs. The combination of MEREC and RS is applied to assess the objective and subjective weighting values of various parameters for AFV assessment. The DNMA approach is utilized to prioritize the different AFVs over various significant parameters. According to the outcomes, the most significant parameters for AFV assessment are social benefits, fueling/charging infrastructure, and financial incentives, respectively. In this context, globally existing AFVs for the sustainable transportation sector are identified, and then prioritized against fifteen different criteria relevant to the environmental, economic, technological, social, and political aspects of sustainability. It is distinguished that electric vehicles ( G 2 ), hybrid electric vehicles ( G 1 ), and hydrogen vehicles ( G 3 ) achieve higher overall performance compared to the other technologies available in India. The assessment outcomes prove that electric vehicles can serve as a valuable alternative for decreasing carbon emissions and negative effects on the environment. This technology contributes to transportation sector development and job creation in less developed areas of the country. Moreover, a comparison with existing studies and a sensitivity investigation are conferred to reveal the robustness and stability of the developed framework.

Keywords: sustainable road transportation; alternative fuel vehicles; intuitionistic fuzzy sets; MEREC; RS; DNMA; multi-attribute decision-analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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