Abstract
This paper proposes an approach to solve Multiple Criteria Decision-making (MCDM) problems when the data given by expert is Interval-Valued Intuitionistic Fuzzy (IVIF) information. A decision-making model is constructed by using the distance measure: Normalized Jaccard distance measure. The robustness of the model is illustrated and validated through numerical example. Further, the problem of choosing best e-learning tool in higher education is considered as a case study.
Highlights
INTRODUCTIONSs introduced by Atanassov and Gargov [1] have substantial benefit of handling with vague and imperfect data and are ingeniously useful in various fields, in decision-making
Inspired by the applicability of Jaccard index in decision making, we proposed a distance measure entitled Normalized Jaccard distance for IVIFSs and presented a model using this distance measure to solve decision making problems
The IVIFSs are proven to be effective in expressing the uncertain information effectively and Jaccard similarity measure gives a very intuitive similarity amount between the samples
Summary
Ss introduced by Atanassov and Gargov [1] have substantial benefit of handling with vague and imperfect data and are ingeniously useful in various fields, in decision-making. Several ranking methodologies are proposed by many researchers in decision making in the form of accuracy functions, score functions and distance measures. The distance based similarity measures and entropy measures are extensively applied in fuzzy decision problems as they specify the degree of evenness while ranking. Selecting a best platform for online-learning has become a significant problem in education sector. The problem of choosing best e-learning tool in higher education is studied using the proposed model.
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