Interval-Valued Picture Fuzzy Maclaurin Symmetric Mean Operator with application in Multiple Attribute Decision-Making

Abstract

A lot of fuzzy models have been planned and researched to review the information under uncertainty and ambiguity. Among these, the model of the interval-valued picture fuzzy set (IVPFS) is very important which can explain the information by four possibilities in the opinion of experts using a membership degree (MD), non-membership degree (NMD), abstinence degree (AD), and a refusal degree (RD) in the form of intervals. The gathering of data is difficult all the time, particularly when the difference of opinions is connected. This article aims to explore the idea of a Maclaurin symmetric mean (MSM) operator in the framework of IVPFS. In this article, we have studied MSM in the framework of IVPFSs and discussed their application in picking the most suitable company benefit plan (CBP) using interval-valued picture fuzzy (IVPF) data. The proposed operators IVPF MSM (IVPFMSM), IVPF weighted MSM (IVPFWMSM), IVPF dual MSM (IVPFDMSM), and IVPF dual weighted MSM (IVPFDWMSM) operators are found trustworthy with the basic properties. Finally, to show the proposed method's importance and significance, a numerical example has been provided and results have been compared with some existing operators.