Intuitionistic Fuzzy Multi-attribute Decision-making Based on the New Entropy and Improved TOPSIS

Qiqing Wang (), Jiahang Yuan and Cunbin Li
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Qiqing Wang: State Grid Energy Research Institute
Jiahang Yuan: North China Electric Power University, School of Economics and Management
Cunbin Li: North China Electric Power University, School of Economics and Management

A chapter in Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024), 2024, pp 1298-1308 from Springer

Abstract: Abstract Given the limitations of current research on intuitionistic fuzzy entropy, which often overlook the hesitancy and uncertainty degrees, this paper introduces a novel intuitionistic fuzzy entropy that accounts for both deviation and hesitancy degrees. Subsequently, a multi-attribute decision-making model is developed, incorporating this new entropy and an enhanced TOPSIS method. The attribute weights are derived using both the entropy weight method and an optimal model that minimizes entropy. To improve the TOPSIS method, grey relational analysis is employed instead of the traditional distance from the positive-negative ideal solution, measuring the closeness of alternatives to these ideal solutions. Finally, two examples are provided to demonstrate the effectiveness of our proposed method.

Keywords: intuitionistic fuzzy sets; intuitionistic fuzzy entropy; improved TOPSIS; grey correlation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-570-6_130

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DOI: 10.2991/978-94-6463-570-6_130

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