Robust Aggregation Operators for Intuitionistic Fuzzy Hypersoft Set with Their Application to Solve MCDM Problem

Abstract

In this paper, we investigate the multi-criteria decision-making complications under intuitionistic fuzzy hypersoft set (IFHSS) information. The IFHSS is a proper extension of the intuitionistic fuzzy soft set (IFSS) which discusses the parametrization of multi-sub attributes of considered parameters, and accommodates more hesitation comparative to IFSS utilizing the multi sub-attributes of the considered parameters. The main objective of this research is to introduce operational laws for intuitionistic fuzzy hypersoft numbers (IFHSNs). Additionally, based on developed operational laws two aggregation operators (AOs), i.e., intuitionistic fuzzy hypersoft weighted average (IFHSWA) and intuitionistic fuzzy hypersoft weighted geometric (IFHSWG), operators have been presented with their fundamental properties. Furthermore, a decision-making approach has been established utilizing our developed aggregation operators (AOs). Through the established approach, a technique for solving decision-making (DM) complications is proposed to select sustainable suppliers in sustainable supply chain management (SSCM). Moreover, a numerical description is presented to ensure the validity and usability of the proposed technique in the DM process. The practicality, effectivity, and flexibility of the current approach are demonstrated through comparative analysis with the assistance of some prevailing studies.

Multicriteria Decision-Making Approach for Aggregation Operators of Pythagorean Fuzzy Hypersoft Sets

“…Also, these operators are unable to handle the multi-subattributes of the considered parameters. The prevailing IFHSWA and IFHSWG [ 34 ] operators capably deal comparatively above-discussed operators considering the multi-subattributes. But, when the sum of Mem and Nmem values of the multi-subattributes exceeds one, then the available IFHSS cannot handle the scenario.…”

“…Whenever the sum of MD and NMD of the multi-subattributes of the alternatives exceeded one, then the above-defined IFHSS is unable to handle the circumstances. To handle this scenario, Zulqarnain et al [ 34 ] developed the PFHSS given as follows.…”

“…They also proposed a MADM technique to resolve decision-making difficulties. Zulqarnain et al [ 33 , 34 ] established the CC, WCC, and AOs for IFHSSs and established the TOPSIS method to solve MADM problems based on their developed correlation measures. Zulqarnain et al [ 35 ] established the TOPSIS approach for PFHSSs utilizing the CC and WCC.…”

Aggregation Operators for Interval-Valued Intuitionistic Fuzzy Hypersoft Set with Their Application in Material Selection

“…Zulqarnain et al [42] extended the TOPSIS approach using the correlation coefficient for IFHSS to solve MADM complications. Zulqarnain et al [43] prolonged the AOs for the IFHSS setting and established a DM technique based on their developed AOs. Jafar et al [44] developed the intuitionistic fuzzy hypersoft matrices with fundamental operations.…”

Bipolar Hypersoft Sets

“…For instance, the fuzzy hypersoft set [35,39], intuitionistic fuzzy hypersoft set [35,40], neutrosophic hypersoft set [35,41], plithogenic hypersoft set [35], convex hypersoft sets and concave hypersoft sets [42] are some of the focuses of certain studies. Recently, several researchers have auspiciously adapted the hypersoft set theory in various fields (see Martin et al [43], Zulqarnain et al [44,45], Ahmad et al [46], Zhang [27], Deli [47], Al-Tahan et al [48], Saqlain et al [49] and Rahman et al [50]).…”