The objective of this work is to present a novel multi-attribute decision making (MADM) method under interval-valued intuitionistic fuzzy (IVIF) set environment by integrating a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Set pair analysis (SPA) theory is the modern uncertainty theory which is composed by the three components, namely “identity”, “discrepancy” and “contrary” degrees of the connection number (CN) and overlap with the various existing theories for handling the uncertainties in the data. Thus, motivated by this, in the present work, an attempt is made to enrich the theory of information measure by presented some exponential based distance measures using CNs of the IVIF sets. The supremacy of the proposed measure is also discussed. Afterward, a TOPSIS method based on the proposed distance measures is developed to solve MADM problem under IVIF environment where each of the element is characteristics by IVIF numbers. The utility, as well as supremacy of the approach, is confirmed through a real-life numerical example and validate it by comparing their results with the several existing approaches results.

中文翻译：

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一种基于SPA理论连接数的区间直觉模糊集指数距离及其基于TOPSIS方法

这项工作的目的是通过集成与理想解决方案相似的顺序偏好技术（TOPSIS）方法，在区间值直觉模糊（IVIF）集环境下提出一种新的多属性决策（MADM）方法。集合对分析（SPA）理论是现代不确定性理论，它由连接数（CN）的“同一性”、“差异”和“相反”度三个部分组成，并与现有的各种处理不确定性的理论重叠。数据的不确定性。因此，受此启发，在目前的工作中，尝试通过使用 IVIF 集的 CN 提出一些基于指数的距离度量来丰富信息度量的理论。还讨论了所提议措施的至高无上性。之后，开发了一种基于所提出的距离度量的 TOPSIS 方法来解决 IVIF 环境下的 MADM 问题，其中每个元素都具有 IVIF 数的特征。该方法的实用性和优越性通过一个真实的数值例子得到证实，并通过将它们的结果与几种现有方法的结果进行比较来验证它。