Multiperson Decision-Making Using Consistent Interval-Valued Fuzzy Information with Application in Supplier Selection

This study describes a consistency-based approach for multiperson decision-making (MPDM) in which decision-makers’ suggestions are expressed as incomplete interval-valued fuzzy preference relations. The presented utilizes Lukasiewicz’s t-norm conjunction with additive reciprocity to obtain comprehensive interval valued relations from each expert, and the transitive closure formula also produces L-consistency. We would evaluate consistency weights of experts using analysis. Experts allocated final priority by combining preset weights. A collective matrix is then constructed weighted sum matrices. After computing possibility degrees, normalization procedure utilized generate complimentary matrices, ranking values alternatives derived well. Finally, numerical example demonstrates efficacy suggested following comparison