Group Decision Making Through Interval Valued Intuitionistic Fuzzy Soft Sets

B. Tripathy, T. R. Sooraj, R. Mohanty, Abhilash Panigrahi
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引用次数: 3

Abstract

This article describes how the lack of adequate parametrization in some of the earlier uncertainty based models like fuzzy sets, rough sets motivated Molodtsov to introduce a new model in soft set. A suitable combination of individual models leads to hybrid models, which are more efficient than their individual components. So, the authors find the introduction of many hybrid models of soft sets, like the fuzzy soft set (FSS), intuitionistic fuzzy soft sets (IFSS), interval valued fuzzy soft set (IVFSS) and the interval valued intuitionistic fuzzy soft set (IVIFSS). Following the characteristic function approach to define soft sets introduced by Tripathy et al., they re-define IVIFSS in this article. One of the most attractive applications of soft set theory and its hybrid models has been decision making in the form of individual decision making or group decision making. Here, the authors propose a group decision making algorithm using IVIFSS, which generalises many of our earlier algorithms. They compute its complexity and establish the computation experimentally with graphical illustrations.
区间值直觉模糊软集的群体决策
本文描述了一些早期基于不确定性的模型(如模糊集、粗糙集)缺乏足够的参数化是如何促使Molodtsov在软集中引入新模型的。单个模型的适当组合导致混合模型,它比单个组件更有效。因此,作者发现了许多软集混合模型的引入,如模糊软集(FSS)、直觉模糊软集(IFSS)、区间值模糊软集(IVFSS)和区间值直觉模糊软集(IVIFSS)。根据Tripathy等人介绍的定义软集的特征函数方法,他们在本文中重新定义了IVIFSS。软集理论及其混合模型最具吸引力的应用之一是个体决策或群体决策。在这里,作者提出了一个使用IVIFSS的群体决策算法,它推广了我们早期的许多算法。他们计算了它的复杂度,并用图形说明建立了实验计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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