فهرست نشریات علمی دسترسی آزاد ایران

The paper presents an Multi-Criteria Decision-Making (MCDM) problem-solving strategy to select the best E-Car. The selection of an E-Car is very important in the present day of an acute energy crisis. Because of the growing demand for transport vehicles in countries like India with a huge population, dependence on fossil fuels is rapidly increasing from day to day, leading to a serious energy crisis. The main objective of the paper is to use the triangular fuzzy neutrosophic number weighted arithmetic aggregation operator and triangular fuzzy neutrosophic number geometric aggregation operator to present a new novel decision-making strategy in selecting the best E-Car. This paper uses the Triangular Fuzzy Number Neutrosophic Hybrid Weighted Arithmetic Geometric Aggregation (TFNNHWAGA) operator, which is a new notion in the field of aggregation operators, and presents some of its basic properties. Score and Accuracy functions are presented in the Triangular Fuzzy Number Neutrosophic (TFNN) environment for deneutrosiphication purposes. The method followed in this paper is innovative as it follows sequential steps of rating the different alternatives in terms of TFNNs against contradictory criteria involved in an uncertain environment. This step uses objective criteria weights as proposed by the decision-maker. Secondly, using the TFNNHWAGA operator, the fuzzy scores are aggregated, and finally, using the proposed score and accuracy function, the best alternative is chosen depending on the highest value of the score function. Lastly, by utilizing the newly developed decision-making strategy based on the neutrosophic hybrid aggregation operator, the solution of an electric car selection problem as an MCDM problem-solving strategy has been presented with an extensive sensitivity analysis to demonstrate the impact of Operator Power Exponent (OPE) and weights of the criteria in finding the ranks of the alternatives. The study is innovative as it develops a new MCDM strategy based on the proposed operator. The newly proposed aggregation operator is more applicable to promote better results in the best alternative selection strategy involving truth, indeterminacy, and falsity components in an uncertain environment. The strategy gives a significant result of selecting the best E-Car among several E-Cars running in the market, judged on several criteria like low operating cost, mileage, storage, engine efficiency, etc involved which is an extraordinarily difficult task in common practice. This reflects the utility and robust applicability of the developed strategy in uncertain environments. A table of comparative analysis has been presented to compare our obtained results with those using other aggregation operators present in the literature applicable in the TENN environment. Different graphs have been included to present graphical variations of score and accuracy functions obtained in different sets of observations.