Abstract
The bipolar neutrosophic set is a suitable instrument to tackle the information with vagueness, complexity, and uncertainty. In this study, we improved the original EDAS (the evaluation based on distance from average solution) with bipolar neutrosophic numbers (BNNs) for a multiple-criteria group decision-making (MCGDM) problem. We calculated the average solution under all the criteria by two existing aggregation operators of BNNs. Then, we computed the positive distance and the negative distance from each alternative to the average ideal solution and determined the appraisal score of alternatives. Based on these scores, we obtained the ranking result. Finally, we demonstrated the practicability, stability, and capability of the improved EDAS method by analyzing the influence parameters and comparing results with an extended VIKOR method.
Highlights
Zadeh first defined the theory of fuzzy set (FS) [1] to represent the uncertain information through the membership function
Studies e concept of bipolar neutrosophic numbers (BNNs) is a suitable instrument in expressing the cases with vagueness, inconsistent, incomplete, and indeterminate information, which widely prevail in various decision-making problems
In this manuscript, based on the original EDAS [35], we develop an improved EDAS for multiple-criteria group decision-making (MCGDM) problems described by BNNs. is method calculates the average alternative by aggregating the BNNs for each criterion using the bipolar neutrosophic number weighted average (BNNWA) and bipolar neutrosophic number weighted geometric (BNNWG) operators
Summary
Zadeh first defined the theory of fuzzy set (FS) [1] to represent the uncertain information through the membership function. E abovementioned analysis [5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39] outlines the motivation of this study to propose a novel EDAS approach in the BNS environment for dealing with MCGDM problems. We improve an EDAS method to tackle an MCGDM problem in which the decision makers (DMs) evaluate the information under the BNS environment.
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