A Novel Weighted Averaging Operator of Linguistic Interval-Valued Intuitionistic Fuzzy Numbers for Cognitively Inspired Decision-Making

Abstract An aggregation operator of linguistic interval-valued intuitionistic fuzzy numbers (LIVIFNs) is an important tool for solving cognitively inspired decision-making problems with LIVIFNs. So far, many operators LIVIFNs have been presented. Each these works well in its specific context. But they are not always monotone because their operational rules invariant and persistent. Dempster-Shafer evidence theory, a general framework modelling epistemic uncertainty, was found to provide the capability overcome limitations. In this paper, weighted averaging based on theory proposed. Firstly, introduced into environment definition under given. Based this, four novel developed proved be Using rules, new constructed monotone. operator, method The application presented illustrated via numerical example. effectiveness advantage demonstrated quantitative comparisons several existing methods. For example, best alternative determined by exactly same as that other comparison some problems, only can generate intuitive ranking results. demonstration results suggest effective Furthermore, will produce counterintuitive since persistent