Power of Continuous Triangular Norms with Application to Intuitionistic Fuzzy Information Aggregation

TL;DR

This paper investigates the power operation of continuous t-norms, develops new intuitionistic fuzzy set aggregation methods, and applies them to improve decision-making processes, addressing theoretical gaps and enhancing practical utility.

Contribution

It provides a systematic theoretical analysis of power stability of continuous t-norms and introduces novel aggregation operators for intuitionistic fuzzy sets with practical decision-making applications.

Findings

Power stability characterized for continuous t-norms.

Derived computational formulas for t-norm powers.

Designed a decision-making algorithm with improved boundary indiscernibility handling.

Abstract

The power operation of continuous Archimedean triangular norms (t-norms) is fundamental for generalizing the multiplication and power operations of intuitionistic fuzzy sets (IFSs) within the framework of continuous Archimedean t-norms. However, due to the lack of systematic research on the power operation of general continuous t-norms in theory, it greatly limits the further generalization of the multiplication and power operations for IFSs via general continuous t-norms. This paper aims to investigate the power operation of continuous t-norms and develop some IF information aggregation methods. In theory, it is proved that a continuous t-norm is power stable if and only if every point is a power stable point, and if and only if it is the minimum t-norm, or it is strict, or it is an ordinal sum of strict t-norms. Moreover, the representation theorem of continuous t-norms is used to obtain the computational formula for the power of continuous t-norms. Based on the power operation of t-norms, four fundamental operations induced by a continuous t-norm for the IFSs are introduced. Furthermore, various IF aggregation operators based on these four fundamental operations, namely the IF weighted average (IFWA), IF weighted geometric (IFWG), and IF mean weighted average and geometric (IFMWAG) operators, are defined, and their properties are analyzed. In application, a new decision-making algorithm is designed based on the IFMWAG operator, which can remove the hindrance of indiscernibility on the boundaries of some classical aggregation operators. The practical applicability, comparative analysis, and advantages of the study with other decision-making methods are furnished to ascertain the efficacy of the designed method.