Algorithm for solving the decision-making problems based on correlation coefficients under cubic intuitionistic fuzzy information: a case study in watershed hydrological system

Harish Garg,Gagandeep Kaur

doi:10.1007/s40747-021-00339-4

Abstract

Cubic intuitionistic fuzzy sets (CIFSs) are a powerful and relevant medium for expressing imprecise information to solve the decision-making problems. The conspicuous feature of their mathematical concept is that it considers simultaneously the hallmarks of both the intuitionistic fuzzy sets (IFSs) and interval-valued IFSs. The present paper is divided into two parts: (i) defining the correlation measures for the CIFSs; (ii) introducing the decision-making algorithm for the CIFS information. Furthermore, few of the fundamental properties of these measures are examined in detail. Based on this, we define a novel algorithm to solve the multi-criteria decision-making process and illustrate numerical examples related to watershed’s hydrological geographical areas, global recruitment problem and so on. A contrastive analysis with several existing studies is also administered to test the effectiveness and verify the proposed method.

Highlights

With the increasing and growing challenges of these days during the decision-making process, it is more difficult to choose the most appropriate or suitable alternative from a set of feasible ones
The symbol × represents the failure of the environment to capture the specific environment and the symbol shows the ability of the environment over the other ones
It can be clearly seen that the approaches based on interval-valued IFSs (IVIFSs) cannot capture the data which is available in the format of Cubic intuitionistic fuzzy sets (CIFSs) and the decision methodologies based on intuitionistic fuzzy sets (IFSs) cannot withstand the situations where experts provide preference values either in the form of IVIFSs or CIFSs

Summary

Introduction

With the increasing and growing challenges of these days during the decision-making process, it is more difficult to choose the most appropriate or suitable alternative from a set of feasible ones. In the context of modern decisionmaking problems, different experts have taken different ways of assessing objects such as crisp and interval, which may be difficult to make a decision. Addressing data uncertainties, the theory of fuzzy set (FS) [1] and its extensions such as intuitionistic fuzzy sets (IFSs) [2], interval-valued IFSs (IVIFSs) [3] are widely used by researchers. Information measures play a vital role in consolidating the distinct choices of the recipients and have been widely studied.

Objectives

Methods

Conclusion