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The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making

机译:区间值直觉模糊集的基于包含的TOPSIS方法用于多准则组决策

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The technique for order preference by similarity to ideal solution (TOPSIS) method is a well-known compromising method for multiple criteria decision analysis. This paper develops an extended TOPSIS method with an inclusion comparison approach for addressing multiple criteria group decision-making problems in the framework of interval-valued intuitionistic fuzzy sets. Considering the relative agreement degrees and the importance weights of multiple decision makers, this paper presents a modified hybrid averaging method with an inclusion-based ordered weighted averaging operation for forming a collective decision environment. Based on the main structure of the TOPSIS method, this paper utilizes the concept of inclusion comparison possibilities to propose a new index for an inclusion-based closeness coefficient for ranking the alternatives. Additionally, two optimization models are established to determine the criterion weights for addressing situations in which the preference information is completely unknown or incompletely known. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a medical group decision-making problem. (C) 2014 Elsevier B.V. All rights reserved.
机译:通过类似于理想解决方案(TOPSIS)方法的顺序偏好技术是一种用于多准则决策分析的众所周知的折衷方法。本文提出了一种扩展的TOPSIS方法,采用包含比较法来解决区间值直觉模糊集框架中的多准则组决策问题。考虑到多个决策者的相对一致程度和重要性权重,本文提出了一种改进的混合平均方法,该方法具有基于包含的有序加权平均操作,以形成一个集体决策环境。基于TOPSIS方法的主要结构,本文利用夹杂物比较可能性的概念,为基于夹杂物的紧密度系数提出了一种新的指数,用于对备选方案进行排名。另外,建立了两个优化模型来确定用于解决偏好信息完全未知或不完全已知的情况的标准权重。最后,通过医疗小组的决策问题说明了所提出方法的可行性和有效性。 (C)2014 Elsevier B.V.保留所有权利。

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