考虑后悔心理和非合作竞争的异质多属性群体决策

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yang Huang , Meiqiang Wang
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引用次数: 0

摘要

在现实中,为了从一组备选方案中选择最佳方案,通常需要几个专家使用异构信息评估每个备选方案的属性值。从备选方案对评价信息存在后悔心理以及备选方案之间存在非合作竞争关系的角度出发,研究了属性值涉及实数、区间、直觉模糊集、区间2型模糊集和区间值犹豫模糊集的异构多属性群体决策问题。为此,提出了一种基于后悔理论和区间数据包络分析(DEA)博弈交叉效率模型的HMAGDM方法。该方法采用先聚合后探索的过程。在聚合阶段,构建基于后悔理论的专家权重确定模型,导出专家权重,并将专家提供的个体决策矩阵进一步聚合为集体决策矩阵。然后,将集体决策矩阵中的异构信息统一转换为区间,将区间表示为参数未知的变量。根据这些变量,提出了基于后悔理论的区间DEA博弈交叉效率模型,计算方案的综合价值,从而对方案进行排序。最后通过供应商选择实例验证了该方法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considering regret psychology and non-cooperative competition among alternatives for heterogeneous multi-attribute group decision making
In reality, to select the best one from a set of alternatives, there are widespread situations that require several experts to assess the attribute values of each alternative with heterogeneous information. The purpose of this paper is to solve the heterogeneous multi-attribute group decision making (HMAGDM) problems with attribute values involving real numbers, intervals, intuitionistic fuzzy sets, interval type-2 fuzzy sets, and interval-valued hesitant fuzzy sets from the perspective that alternatives have regret psychology with respect to the assessment information and that there is a non-cooperative competitive relationship among alternatives. Therefore, a method based on regret theory and interval data envelopment analysis (DEA) game cross-efficiency model is proposed for HMAGDM. The method adopts a process of aggregation followed by exploration. In the aggregation phase, a regret theory-based expert weight determination model is constructed to derive the weights of experts, and the individual decision matrices provided by individual experts are further aggregated into a collective decision matrix. Then, the heterogeneous information in the collective decision matrix is uniformly converted into intervals, which are represented as variables with unknown parameters. According to these variables, a regret theory-based interval DEA game cross-efficiency model is proposed to calculate the comprehensive values of alternatives and thus rank alternatives. The feasibility and effectiveness of the proposed method are illustrated by a supplier selection example.
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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