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A new distance measure for interval valued intuitionistic fuzzy sets and its application to group decision making problems with incomplete weights information

机译:区间直觉模糊集的一种新的距离测度及其在权值不完全的群决策中的应用。

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摘要

The aim of this study is to introduce a novel generalized distance measure for interval valued intuitionistic fuzzy sets and to illustrate the applicability of the proposed distance measure to group decision making problems. Firstly, a generalized distance measure is proposed along with proofs satisfying its axioms. Then, a comparison between the proposed distance measure and well-known distance measures is performed in terms of counter-intuitive cases. Subsequently, the extension of TOPSIS method, in which the proposed distance measure is used to calculate separation measures, to an interval valued intuitionistic fuzzy (IVIF) environment is demonstrated to solve multi-criteria group decision making (MCGDM) problems using optimal criteria weights determined with linear programming model based on the concept of maximizing relative closeness coefficient. Finally, two illustrative examples are provided for proof-of concept purposes and to demonstrate benefits of using the proposed distance measure over the existing ones in IVIF TOPSIS method for MCGDM problems. (C) 2015 Elsevier B.V. All rights reserved.
机译:这项研究的目的是为区间值直觉模糊集引入一种新颖的广义距离测度,并说明所提出的距离测度对群体决策问题的适用性。首先,提出了广义距离测度以及满足其公理的证明。然后,根据反直觉的情况对建议的距离度量和众所周知的距离度量进行比较。随后,证明了将TOPSIS方法扩展到区间值直觉模糊(IVIF)环境中的方法,该方法将拟议的距离度量用于计算分离度量,以使用确定的最佳标准权重来解决多准则组决策(MCGDM)问题线性规划模型基于最大化相对接近系数的概念。最后,提供了两个说明性示例,以用于概念验证的目的,并展示了针对MCGDM问题,使用建议的距离度量优于IVIF TOPSIS方法中的现有距离度量。 (C)2015 Elsevier B.V.保留所有权利。

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