Cross-Entropy and Prioritized Aggregation Operator with Simplified Neutrosophic Sets and Their Application in Multi-Criteria Decision-Making Problems

Simplified neutrosophic sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified neutr...

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Bibliographic Details
Published inInternational journal of fuzzy systems Vol. 18; no. 6; pp. 1104 - 1116
Main Authors Wu, Xiao-hui, Wang, Jian-qiang, Peng, Juan-juan, Chen, Xiao-hong
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016
Springer Nature B.V
Subjects
Artificial Intelligence
Automobile industry
Computational Intelligence
Decision making
Engineering
Entropy
Fuzzy sets
Linguistics
Management Science
Methods
Multiple criteria decision making
Multiple criterion
Operations Research
Pattern recognition
Prioritized aggregation operator
Simplified neutrosophic sets
Cross-entropy
Multi-criteria decision-making
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Summary:Simplified neutrosophic sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified neutrosophic environment. First, the prioritized weighted average operator and prioritized weighted geometric operator for simplified neutrosophic numbers (SNNs) are defined, and the related theorems are also proved. Then two novel effective cross-entropy measures for SNSs are proposed, and their properties are proved as well. Furthermore, based on the proposed prioritized aggregation operators and cross-entropy measures, the ranking methods for SNSs are established in order to solve MCDM problems. Finally, a practical MCDM example for coping with supplier selection of an automotive company is used to demonstrate the effectiveness of the developed methods. Moreover, the same example-based comparison analysis of between the proposed methods and other existing methods is carried out.
ISSN:1562-2479
2199-3211
DOI:10.1007/s40815-016-0180-2