English

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

Artificial Intelligence 2016-12-05 v4

Abstract

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.

Cite

@article{arxiv.1607.01254,
  title  = {An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers},
  author = {Jagannath Roy and Ananta Ranjan and Animesh Debnath and Samarjit Kar},
  journal= {arXiv preprint arXiv:1607.01254},
  year   = {2016}
}

Comments

14 pages

R2 v1 2026-06-22T14:43:25.443Z