Abstract This article contributes to the advancement and evolution of outranking decision-making methodologies, with a novel essay on ELimination Choice Translating REality (ELECTRE) family methods. Its primary target is unfold constituents expound implementation ELECTRE II method for group decision making in complex Pythagorean fuzzy framework. results method. By inception, it intrinsically su...

The purpose of this article is to analyze the current state research in field fuzzymulticriteria optimization methods, as well development aggregation operators and algorithmsusing fuzzy multicriteria group decision-making using an intuitionistic attitude linguisticpreferences. most well-known methods are presented:ELECTRE, PROMETHEE, VIKOR, TOPSIS, AHP, ANP, MACBETH, DEMATEL, Shoke integraland...

Abstract The recommendation systems plays an important role in today’s life as it assist reliable selection of common utilities. code system is being used by the databases (GitHub, source frog etc.) aiming to recommend more appropriate users. There are several factors that could negatively impact performance (CRS). This study aims empirically explore challenges have critical on CRS. Using syste...

Multicriteria decision making (MCDM) is one of the methods that popularly has been used in solving personnel selection problem. Alternatives, criteria, and weights are some of the fundamental aspects in MCDM that need to be defined clearly in order to achieve a good result. Apart from these aspects, fuzzy data has to take into consideration that it may arise from unobtainable and incomplete inf...

Recently, a new model based on Pythagorean fuzzy set (PFS) has been presented to manage the uncertainty in real-world decision-making problems. PFS has much stronger ability than intuitionistic fuzzy set to model such uncertainty. In this paper, we define some novel operational laws of PFSs and discuss their desirable properties. For the multicriteria decision-making problems with PFSs, we prop...

For a fixed finite universe U = {u1, . . . , un}, a fuzzy subset F of U is given by its membership function F : U → [0, 1] (we will not distinguish fuzzy subsets and the corresponding membership functions notations). For several practical purposes, especially in multicriteria decision making, the expected value E(F ) of F should be introduced. The original Zadeh approach in [11] was based on a ...