Information Measures-Based Multi-criteria Decision-Making Problems for Interval-Valued Intuitionistic Fuzzy Environment
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RESEARCH ARTICLE
Information Measures-Based Multi-criteria Decision-Making Problems for Interval-Valued Intuitionistic Fuzzy Environment Pratibha Rani1 • Divya Jain2
Received: 20 August 2016 / Revised: 29 January 2019 / Accepted: 5 February 2019 The National Academy of Sciences, India 2019
Abstract In the present communication, new entropy and divergence measures are developed for interval-valued intuitionistic fuzzy sets and compared it with the existing measures. Numerical result reveals that the proposed entropy measure attains the accurate classification, which illustrates their efficiency. Further, to cope with the multicriteria decision-making problems with non-commensurable and conflicting criteria, an extended VIKOR method is developed under interval-valued intuitionistic
Significance of Proposed Research At the present time, the development of information technology leads to increase the number of alternatives, so that the decision making is more difficult and uncertain in real-life problems. In industries, it is very important to select an optimal supplier which maintains the good coordination between management and supplier with respect to cost, quality, quantity and time. Multi-criteria decision making, a part of decision making, is a process of selecting an optimal alternative among a set of alternatives concerning multiple conflicting criteria. In this paper, a multi-criteria decision-making approach, named as interval-valued intuitionistic fuzzy VIKOR, is developed to find the best supplier under uncertain environment. The proposed method can also be applied in the evaluation of renewable energy resources, flood reservoir management policies, sustainable ecosystem management strategies, service quality for vehicle insurance companies and township development in urban planning. The divergence and entropy measures used in this paper can be used for feature extraction, data mining, pattern recognition, image segmentation and medical diagnosis. & Pratibha Rani [email protected] Divya Jain [email protected] 1
Department of Mathematics, Marwadi University, Rajkot, GJ, India
2
Department of Mathematics, Jaypee University of Engineering and Technology, Guna, M.P., India
environment. On the basis of proposed divergence measure, the particular measure of closeness of each alternative is calculated to the interval-valued intuitionistic fuzzy positive ideal solution. To illustrate the applicability of the proposed method, a multi-criteria decision-making problem of supplier selection is discussed under incomplete and uncertain information situation, which employs its advantages and feasibility. Keywords Divergence measure Entropy Interval-valued intuitionistic fuzzy set MCDM VIKOR
1 Introduction Multi-criteria decision making (MCDM), an important part of decision making, is a usual human activity of making decisions by choosing, ranking or sorting the alternatives from a set of feasible alternatives with respect to a set of conflicting criteria. The existing studies witnessed the rapid
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