An unified fuzzy decision strategy for analysing green fuel alternatives: A road to long-term development

Abstract

The transportation industry is critical to the economic prosperity of the country. The use of conventional fuels for transportation is hampered by a number of factors, including an insufficiency of fossil fuels, switching crude oil prices, urbanization, and strict environmental regulations. This has sparked a global search for cleaner fuel alternatives that can meet energy requirements and tackle sustainability issues. The development of decision-support tools aid in tackling the issue by studying the difficulties encountered in selecting a better fuel alternative that provides environmental advantages and promotes sustainable mobility. This work attempts to analyse multi-criteria decision making concerns using aggregation operators from the perspective of a linear diophantine hesitant fuzzy setting. The linear diophantine hesitant fuzzy weighted average operator and linear diophantine hesitant fuzzy weighted geometric operator is designed to aggregate linear diophantine hesitant fuzzy data. Furthermore, an integrated model was developed in an attempt to evaluate the value of aggregation operators based on linear diophantine fuzzy sets while taking into account the various clean fuel sources for transportation in India. The versatility and efficacy of the framework are further substantiated by a comparative and susceptibility analysis.