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

The purpose of this paper is to study a type-2 fuzzy multi-attribute decision making (MADM) methodology. Multi-Attributive Border Approximation area Comparison (MABAC) method is extended for MADM based on trapezoidal interval type-2 fuzzy numbers (TrIT2FNs).This method is a pragmatic and reliable tool for rational decision making due to its own characteristics. A systematic evaluation and assessment method is developed in this paper by integrating TrIT2FNs and used for evaluation and selection of the most suitable candidate for a software company which is heading to hire a system analysis engineer based on few attributes. The performance ratings of alternative candidates and the weights of the criteria are evaluated based on decision makers from different expertise. The validity and feasibility of the proposed method are illustrated by an example and finally compared with two other MADM methods.