An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

Green supplier selection is an important debate in green supply chain management(GSCM),attracting global attention from scholars,especially companies and policymakers.Companies frequently search for new ideas and strategies to assist them in realizing sustainable development.Because of the speculative character of human opinions,supplier selection frequently includes unreliable data,and the interval-valued Pythagorean fuzzy soft set(IVPFSS)provides an exceptional capacity to cope with excessive fuzziness,inconsistency,and inexactness through the decision-making procedure.The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers(IVPFSNs)and create two interaction operators-the intervalvalued Pythagorean fuzzy soft interaction weighted average(IVPFSIWA)and the interval-valued Pythagorean fuzzy soft interaction weighted geometric(IVPFSIWG)operators,and analyze their properties.These operators are highly advantageous in addressing uncertain problems by considering membership and non-membership values within intervals,providing a superior solution to other methods.Moreover,specialist judgments were calculated by the MCGDM technique,supporting the use of interaction AOs to regulate the interdependence and fundamental partiality of green supplier assessment aspects.Lastly,a statistical clarification of the planned method for green supplier selection is presented.

Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Set with Their Application to Solve Multi-Attribute Group Decision Making Problem

Interval-valued Pythagorean fuzzy soft set(IVPFSS)is a generalization of the interval-valued intuitionistic fuzzy soft set(IVIFSS)and interval-valued Pythagorean fuzzy set(IVPFS).The IVPFSS handled more uncertainty comparative to IVIFSS;it is the most significant technique for explaining fuzzy information in the decision-making process.In this work,some novel operational laws for IVPFSS have been proposed.Based on presented operational laws,two innovative aggregation operators(AOs)have been developed such as interval-valued Pythagorean fuzzy soft weighted average(IVPFSWA)and interval-valued Pythagorean fuzzy soft weighted geometric(IVPFSWG)operators with their fundamental properties.A multi-attribute group decision-making(MAGDM)approach has been established utilizing our developed operators.A numerical example has been presented to ensure the validity of the proposed MAGDM technique.Finally,comparative studies have been given between the proposed approach and some existing studies.The obtained results through comparative studies show that the proposed technique is more credible and reliable than existing approaches.

Partition region-based suppressed fuzzy C-means algorithm

Aimed at the problem that the traditional suppressed fuzzy C-means clustering algorithms ignore the real needs of different objects, applying the same suppressed parameter for modifying membership degrees of all the objects, a novel partition region-based suppressed fuzzy C-means clustering algorithm with better capacity of adaptability and robustness is proposed in this paper. The model based on the real needs of different objects is built, making it clear to decide whether to proceed with further determination; in addition, the external user-defined suppressed parameter is automatically selected according to the intrinsic structural characteristic of each dataset, making the proposed method become robust to the fluctuations in the incoming dataset and initial conditions. Experimental results show that the proposed method is more robust than its counterparts and overcomes the weakness of the original suppressed clustering algorithm in most cases.

双犹豫模糊软集的研究

为对决策过程中犹豫模糊软集参数的非隶属度情况进行有效刻画,结合双犹豫模糊集的非隶属度与软集的参数化特性,提出双犹豫模糊软集的概念。基于双犹豫模糊软集的定义,描述双犹豫模糊软集的补、并、交、拓展交、限制并、且、或、差、平均及几何等运算方法,同时分析对应运算结果并论述相应性质。给出一个基于双犹豫模糊软集的相关性系数算法,解决了双犹豫模糊软集的非隶属度问题。

区间值模糊参数软集及其在决策中的应用

定义了区间值模糊参数软集的概念,研究了区间值模糊参数软集的运算及运算性质。然后,给出利用区间值模糊参数软集进行决策的方法,并通过实例说明了方法的可行性。

模糊参数模糊软R_0-代数

Cagman引入模糊参数模糊软集(简记为fpfs)的概念,该概念是模糊集和软集的推广。本文将这一理论应用到R0-代数中,引入R0-代数的fpfs滤子和fpfs关联滤子的概念,刻画其相应的性质。最后,将聚合算子应用到R0-代数中,为这一理论应用到不确定性问题中奠定理论基础。

模糊参数软区间集及其应用

将模糊参数软集与区间集相结合,定义了模糊参数软区间集的概念,研究了模糊参数软区间集的运算及其性质.然后,给出模糊参数软区间集在决策中的应用,说明了方法的可行性.推广了软区间集的相关研究结果.

犹豫模糊参数软集及其在多属性群体决策中的应用

本文从参数权重的犹豫性角度出发,将犹豫模糊集与软集相结合,首次引入犹豫模糊参数软集的概念,讨论了犹豫模糊参数软集的若干基本运算及其性质。接着,分析了犹豫模糊参数软集、犹豫模糊集、模糊参数软集三者之间的内在联系,在此基础上研究了犹豫模糊参数软集在多属性群体决策中的应用,给出两种不同的决策算法,并通过实例验证了这两种方法的可行性及有效性。