2017
DOI: 10.1007/s12652-017-0548-7
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Neutrosophic AHP-Delphi Group decision making model based on trapezoidal neutrosophic numbers

Abstract: In the proposed model,experts will focus only on (n − 1) restricted judgments and this also enhances the performance of AHP over the traditional version that is proposed by Saaty. A real life example is developed based on expert opinions about evaluation process of many international search engines. The problem is solved to show the validation of the suggested method in neutrosophic path.

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Cited by 80 publications
(40 citation statements)
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“…b. Making comparisons between practices by the first expert and the second expert, as presented in Table 2, and focusing on consensus judgments only on (nÀ1) using a scale (0,1) [35]. 2.…”
Section: The General Steps Of the Proposed Methodsmentioning
confidence: 99%
“…b. Making comparisons between practices by the first expert and the second expert, as presented in Table 2, and focusing on consensus judgments only on (nÀ1) using a scale (0,1) [35]. 2.…”
Section: The General Steps Of the Proposed Methodsmentioning
confidence: 99%
“…Make comparisons between criteria by each expert as shown in Table 1. c. Focuses only on (n − 1) consensus judgments using a scale from 0 to 1 [30,31].…”
Section: Neutrosophic Dematel Approachmentioning
confidence: 99%
“…Especially, in real-world situations of group decisions, the exact appreciation of weights is important for handling MCDM problems and for making a decision. For solving such problems, several studies have attempted to develop the methods to handle the MCDM problems using various kinds of information, such as fuzzy set [1], interval fuzzy set [2,3], intuitionistic fuzzy set [4,5], 2 of 15 hesitant fuzzy set [6], neutrosophic set [7][8][9][10], interval neutrosophic set [11][12][13][14][15], or single neutrosophic set [16], etc. [17][18][19], and various methods (e.g., maximizing deviation method, entropy, optimization method) [20][21][22] in which the information of criteria weights are incompletely known.…”
Section: Introductionmentioning
confidence: 99%
“…(2) Another reason is that the TOPIS model in [13] could not work efficiently without determining the evaluation information of decision-makers and this issue was not considered in [13]. (3) In real application situations, many MCDM problems reflect a lack of weight information for the times, criteria, and decision-makers.…”
Section: Introductionmentioning
confidence: 99%