A strategic decision-making framework for evaluating barriers to green supply chain management using fractional fuzzy similarity measures.

The study of similarity and distance measures plays a key role in understanding the relationships between fuzzy sets and their extensions, especially when applied to decision-making problems. While there has been notable progress in developing similarity measures for various types of generalized fuzzy sets, including fractional fuzzy sets, there is still a lack of well-developed measures suited to the structure of [Formula: see text]fractional fuzzy sets. This limitation reduces the effectiveness of fuzzy models in complex decision-making tasks where uncertainty needs to be handled more carefully and flexibly.

Decision-making algorithm with complex hesitant fuzzy partitioned maclaurin symmetric mean aggregation operators and SWARA method.

Complex hesitant fuzzy sets (CHFSs) have emerged as a powerful tool for addressing uncertainty, especially in representing two-dimensional information through multiple possible values. This study addresses the limitations in existing methodologies by introducing two novel operators: the complex hesitant fuzzy partitioned Maclaurin symmetric mean (CHFPMSM) and the complex hesitant fuzzy weighted partitioned Maclaurin symmetric mean (CHFWPMSM). These operators enable effective aggregation of criteria by organizing them into independent partitions based on inherent properties, enhancing their applicability to real-world multi-criteria decision-making (MCDM) problems.

Correction: An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information.

[This corrects the article DOI: 10.1371/journal.pone.

Interval-valued picture fuzzy decision-making framework with partitioned maclaurin symmetric mean aggregation operators.

Interval-valued picture fuzzy (IVPF) set is an extension of the picture fuzzy set theory used to represent uncertainty and vagueness in the processes of decision-making. This study focuses on exploring the interrelationships among multiple IVPFSs and criteria partitions. We investigate the IVPF partitioned Maclaurin symmetric mean operator and the weighted IVPF partitioned Maclaurin symmetric mean operator and discuss their respective properties.

An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information.

Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and qualitative flexible (QUALIFLEX) methods based on the revised aggregation operators to solve multiple criteria group decision making (MCGDM). To accomplish this, we first revise the extant operational laws of q-RFLSs to make up for their shortcomings. Based on novel operational laws, we develop q-rung orthopair fuzzy 2-tuple linguistic (q-RFL) weighted averaging and geometric operators and provide the corresponding results.

Group decision-making algorithm with sine trigonometric r,s,t-spherical fuzzy aggregation operators and their application.

r, s, t-spherical fuzzy (r, s, t-SPF) sets provide a robust framework for managing uncertainties in decision-making, surpassing other fuzzy sets in their ability to accommodate diverse uncertainties through the incorporation of flexible parameters r, s, and t. Considering these characteristics, this article explores sine trigonometric laws to enhance the applicability and theoretical foundation for r, s, t-SPF setting. Following these laws, several aggregation operators (AOs) are designed for aggregation of the r, s, t-SPF data.

q-Rung orthopair fuzzy 2-tuple linguistic WASPAS algorithm for patients' prioritization based on prioritized Maclaurin symmetric mean aggregation operators.

Due to the fuzziness of the medical field, q-rung orthopair fuzzy 2-tuple linguistic (q-RF2L) set is the privileged way to aid medical professionals in conveying their assessments in the patient prioritization problem. The theme of the present study is to put forward a novel approach centered around the merging of prioritized averaging (PA) and the Maclaurin symmetric mean (MSM) operator within q-RF2L context. According to the prioritization of the professionals and the correlation among the defined criteria, we apply both PA and MSM to assess priority degrees and relationships, respectively.

q-rung orthopair fuzzy 2-tuple linguistic clustering algorithm and its applications to clustering analysis.

q-ROPFLS, including numeric and linguistic data, has a wide range of applications in handling uncertain information. This article aims to investigate q-ROPFL correlation coefficient based on the proposed information energy and covariance formulas. Moreover, considering that different q-ROPFL elements may have varying criteria weights, the weighted correlation coefficient is further explored.