融合属性内部不确定和外部交互的多属性群体决策模型

doi:10.12305/j.issn.1001-506X.2025.06.19

Abstract

Abstract:

Personalized individual semantics represent the different understandings for language terms by different decision-makers, and binary semantics have greater advantages in expressing personalized individual semantics. This paper focuses on the difficulties in designing binary semantic distance measurement and its attribute weights, systematically studying the characteristics of binary semantic distance measurement and proposing a distance measurement formula. Firstly, a dual objective linear programming model is designed based on evidence theory and fuzzy measure, respectively, for the internal uncertainty and external interaction of attributes to solve the comprehensive attribute weights. Secondly, based on the utility value matrix and sorting matrix of alternative solutions, a group decision solving method with binary semantic evaluation values is proposed. Numerical examples and comparative analysis verify that the proposed method can effectively handle the uncertain information and interaction behavior of attributes. The proposed method has strong robustness, making the sorting results more accurate and stable.

Key words: attribute weight, distance measurement, personalized individual semantics, binary semantics

CLC Number:

C934

Jiali WANG, Wenqi JIANG. Multi-attribute group decision-making model integrating internal uncertainty and external interaction of attribute[J]. Systems Engineering and Electronics, 2025, 47(6): 1909-1916.

Figures/Tables 6

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References 40

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φ	方案排序	φ	方案排序
0	A₃≻A₁≻A₂	0.6	A₃≻A₁≻A₂
0.1	A₃≻A₁≻A₂	0.7	A₃≻A₁≻A₂
0.2	A₃≻A₁≻A₂	0.8	A₃≻A₁≻A₂
0.3	A₃≻A₁≻A₂	0.9	A₃≻A₁≻A₂
0.4	A₃≻A₁≻A₂	1.0	A₃≻₁≻A₂
0.5	A₃≻A₁≻A₂	-	-

方法	方案			排序结果
方法	A₁	A₂	A₃	排序结果
本文方法	0.822 0	0.804 6	0.873 8	A₃≻A₁≻A₂
E₁	0.167 0	0.113 3	0.179 9	A₃≻A₁≻A₂
E₂	0.143 7	0.149 6	0.135 7	A₂≻A₁≻A₃
E₃	0.141 0	0.155 6	0.170 4	A₃≻A₂≻A₁
平均得分值	0.31	0.30	0.34	-

方法	方案
方法	A₃和A₁	A₁和A₂	A₂和A₃
本文方法	0.061 9	0.026 0	0.087 9
E₁	0.012 9	0.012 9	0.053 7
E₂	0.008 0	0.005 9	0.013 9
E₃	0.014 8	0.014 6	0.029 4

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Multi-attribute group decision-making model integrating internal uncertainty and external interaction of attribute

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