A New Entropy Measurement for the Analysis of Uncertain Data in MCDA Problems Using Intuitionistic Fuzzy Sets and COPRAS Method

In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, whe...

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Bibliographic Details
Published in:Axioms 2021-12, Vol.10 (4), p.335
Main Authors: Thakur, Parul, Kizielewicz, Bartłomiej, Gandotra, Neeraj, Shekhovtsov, Andrii, Saini, Namita, Saeid, Arsham Borumand, Sałabun, Wojciech
Format: Article
Language:English
Subjects:
COPRAS method
Decision analysis
Decision making
Decision support systems
Energy industry
Entropy
Fuzzy sets
Health care industry
intuitionistic set
MCDM
Methods
Multiple criterion
Municipal solid waste
Renewable resources
Sensitivity analysis
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Summary:In this paper, we propose a new intuitionistic entropy measurement for multi-criteria decision-making (MCDM) problems. The entropy of an intuitionistic fuzzy set (IFS) measures uncertainty related to the data modelling as IFS. The entropy of fuzzy sets is widely used in decision support methods, where dealing with uncertain data grows in importance. The Complex Proportional Assessment (COPRAS) method identifies the preferences and ranking of decisional variants. It also allows for a more comprehensive analysis of complex decision-making problems, where many opposite criteria are observed. This approach allows us to minimize cost and maximize profit in the finally chosen decision (alternative). This paper presents a new entropy measurement for fuzzy intuitionistic sets and an application example using the IFS COPRAS method. The new entropy method was used in the decision-making process to calculate the objective weights. In addition, other entropy methods determining objective weights were also compared with the proposed approach. The presented results allow us to conclude that the new entropy measure can be applied to decision problems in uncertain data environments since the proposed entropy measure is stable and unambiguous.
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms10040335