Nested formulation paradigms for induced ordered weighted averaging aggregation for decision‐making and evaluation

Abstract

Existing extensions to Yager's ordered weighted aver-aging (OWA) operators enlarge the application rangeand to encompass more principles and properties relatedto OWA aggregation. However, these extensions do notprovide a strict and convenient way to model evaluationscenarios with complex or grouped preferences. Basedon earlier studies and recent evolutionary changes inOWA operators, we propose formulation paradigms forinduced OWA aggregation and a related weight functionwith self‐contained properties that make it possibleto model such complex preference‐involved evaluationproblems in a systematic way. The new formulationshave some recursive forms that provide more waysto apply OWA aggregation and deserve further studyfrom a mathematical perspective. In addition, the newproposal generalizes almost all of the well‐knownextensions to the original OWA operators. We providean example showing the representative use of suchparadigms in decision‐making and evaluation problems.