AN INTEGRATED FUZZY BWM-EDAS METHOD FOR MULTIPLE CRITERIA DECISION MAKING PROBLEM WITH NEUTROSOPHIC HESITANT FUZZY INFORMATION AND ITS APPLICATION

Abstract

Abstract:  The goal of this study is to identify risk-free exercises for expectant mothers utilizing the effective multi-criteria decision-making methodology. This paper presents a novel approach for solving a multi-criteria decision-making problem in a neutrosophic hesitant fuzzy environment. The proposed technique is developed by integrating the best worst method (BWM) with the EDAS method (Evaluation based on distance from average solution). In this paper, the Best-Worst method is used to calculate the weights of the criteria and the EDAS method is used for classifying alternatives. The proposed MCDM approach has been applied to the exercise assessment problem.  An numerical example is presented to show the validity and usability of the proposed method. Based on survey data, this exercise assessment problem was developed. This problem evaluates four different types of exercise using the appropriate five criteria, with the goal of determining the safest, risk-free and effective physical activity during pregnancy. The ideal alternative is resolved in light of the results of the proposed procedure. This is a new kind of MCDM problem to integrate EDAS-BWM methodologies in hesitant neutrosophic environments with the context of exercise assessment.