A novel probabilistic linguistic group decision-making method driven by DEA cross-efficiency and trust relationship

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Intelligence Pub Date : 2025-10-18 DOI:10.1007/s10489-025-06696-8

Feifei Jin, Shuyan Guo, Jinpei Liu

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Abstract

In this paper, a new group decision-making (GDM) method is proposed to improve the quality and efficiency of decision-making. This method considers the degree of preference of decision makers (DMs) for different linguistic terms and adopts the probabilistic linguistic preference relations (PLPRs) model. First, a multiplicative consistency adjustment procedure is proposed to obtain a PLPR with acceptable consistency. Then, the trust matrix among experts is used to determine the weight vector of experts and realize the effective integration of information. After obtaining the collective PLPR, a DEA cross-efficiency model is designed to seek the target decision-making units (DMUs), which are the most efficient in the production possibility set. In addition, an integrated GDM method is designed to rank all alternatives adequately. Finally, the numerical analysis is carried out using the real estate company evaluation as an example. Comparative analysis with other methods quantifies the results, which enables us to evaluate the presented GDM method objectively.

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一种基于DEA交叉效率和信任关系的概率语言群体决策方法

为了提高决策质量和效率，本文提出了一种新的群体决策方法。该方法考虑了决策者对不同语言术语的偏好程度，采用了概率语言偏好关系模型。首先，提出了一种乘法一致性调整方法，以获得具有可接受一致性的PLPR。然后，利用专家之间的信任矩阵确定专家的权重向量，实现信息的有效集成。在得到集体PLPR后，设计DEA交叉效率模型，寻求生产可能性集中效率最高的目标决策单元（dmu）。此外，还设计了一种综合GDM方法，对所有备选方案进行充分排序。最后，以房地产公司评价为例进行数值分析。与其他方法的比较分析可以量化结果，使我们能够客观地评价所提出的GDM方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Intelligence 工程技术-计算机：人工智能

CiteScore

6.60

自引率

20.80%

发文量

1361

审稿时长

5.9 months

期刊介绍： With a focus on research in artificial intelligence and neural networks, this journal addresses issues involving solutions of real-life manufacturing, defense, management, government and industrial problems which are too complex to be solved through conventional approaches and require the simulation of intelligent thought processes, heuristics, applications of knowledge, and distributed and parallel processing. The integration of these multiple approaches in solving complex problems is of particular importance. The journal presents new and original research and technological developments, addressing real and complex issues applicable to difficult problems. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.