New Decision-Making Technique Based on Hurwicz Criteria for Fuzzy Ranking

Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using the center of the area (COA) or centroid method. Further, to find the best solution, Hurwicz criteria are used on the defuzzified data. A new decision-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy numbers. The proposed technique considers all types of decision makers' perspectives such as optimistic, neutral, and pessimistic which is crucial in solving decision-making problems. A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among decision-makers. The significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.

Automated summary

Efficient decision-making is a challenge in research, and accuracy can be improved through fuzzification and defuzzification processes. This paper proposes using the COA method and Hurwicz criteria for solving multi-criteria decision-making problems and demonstrates their application through a simple case study.