Compatibility measurement-based group decision making with interval fuzzy preference relations. Issue 1 (March 2017)

• Record Type: Journal Article
• Authors: Zhang, Xue-Yang; Wang, Zhou J
• Is Part Of: Journal of algorithms & computational technology. Volume 11:Issue 1(2017)
• Page Start: 31
• Page End: 39
• Publication Date: 2017-03
• Subjects: Interval fuzzy preference relation -- compatibility -- aggregation -- consensus -- group decision making; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748301816665022
• Languages: English
• ISSNs: 1748-3018

Abstract

In this paper, we put forward a ratio-based compatibility degree between any two ]0, 1[-valued interval numbers to measure how proximate they approach to each other. A compatibility measurement is presented to evaluate the compatibility degree between a pair of ]0, 1[-valued interval fuzzy preference relations (IFPRs). By employing the geometric mean, a measurement formula is proposed to calculate how close one interval fuzzy preference relation is to all the other interval fuzzy preference relations in a group. We devise an induced interval fuzzy ordered weighted geometric (IIFOWG) operator to aggregate ]0, 1[-valued interval numbers, and apply the induced interval fuzzy ordered weighted geometric operator to fuse interval fuzzy preference relations into a collective one. Based on the compatibility measurement between two interval fuzzy preference relations, a notion of acceptable consensus of interval fuzzy preference relations is introduced to check the consensus level between an individual interval fuzzy preference relation and a collective interval fuzzy preference relation, and a novel procedure is developed to handle group decision-making problems with interval fuzzy preference relations. A numerical example with respect to the evaluation of e-commerce websites is provided to illustrate the proposed procedure.