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An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers

In this paper, we attempt to extend Multi Attributive Border Approximation area Comparison (MABAC) approach for multi-attribute decision making (MADM) problems based on type-2 fuzzy sets (IT2FSs). As a special case of IT2FSs interval type-2 trapezoidal fuzzy numbers (IT2TrFNs) are adopted here to deal with uncertainties present in many practical evaluation and selection problems. A systematic description of MABAC based on IT2TrFNs is presented in the current study. The validity and feasibility of the proposed method are illustrated by a practical example of selecting the most suitable candidate for a software company which is heading to hire a system analysis engineer based on few attributes. Finally, a comparison with two other existing MADM methods is described.

preprint2016arXivOpen access
Jagannath RoyAnanta RanjanAnimesh DebnathSamarjit Kar
Artificial Intelligence
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Jagannath RoyAnanta RanjanAnimesh DebnathSamarjit Kar

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