基于累积前景理论的扩展 EDAS 方法，适用于具有区间值直观模糊信息的多属性群体决策

IF 3.3 4区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Informatica Pub Date : 2024-03-15 DOI:10.15388/24-infor547

Jing Wang, Qiang Cai, Guiwu Wei, Ningna Liao

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引用次数: 0

摘要

基于直观模糊集（IFS）的区间值直观模糊集（IVIFS）结合了经典决策方法，其研究和应用备受关注。经过比较分析，我们可以清楚地看到，多种带有 IVIFS 信息的经典方法已被应用于许多实际问题。本文在累积前景理论（CPT）的基础上扩展了经典的 EDAS 方法，考虑了 IVIFS 下决策专家（DEs）的心理因素。考虑到 IVIFS 的模糊性和不确定性以及心理偏好，针对多属性群体决策（MAGDM）问题，创建了一种基于 IVIFS 下 CPT 的原创 EDAS 方法（IVIF-CPT-EDAS）。同时，采用信息熵法评估属性权重。最后，以绿色技术风险投资（GTVC）项目选择为例，通过比较说明了 IVIF-CPT-EDAS 方法的优势，并应用敏感性分析证明了这一新方法的有效性和稳定性。PDF XML

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An Extended EDAS Approach Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-Valued Intuitionistic Fuzzy Information

The interval-valued intuitionistic fuzzy sets (IVIFSs), based on the intuitionistic fuzzy sets (IFSs), combine the classical decision method and its research and application is attracting attention. After a comparative analysis, it becomes clear that multiple classical methods with IVIFSs’ information have been applied to many practical issues. In this paper, we extended the classical EDAS method based on the Cumulative Prospect Theory (CPT) considering the decision experts (DEs)’ psychological factors under IVIFSs. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, an original EDAS method, based on the CPT under IVIFSs (IVIF-CPT-EDAS) method, is created for multiple-attribute group decision making (MAGDM) issues. Meanwhile, the information entropy method is used to evaluate the attribute weight. Finally, a numerical example for Green Technology Venture Capital (GTVC) project selection is given, some comparisons are used to illustrate the advantages of the IVIF-CPT-EDAS method and a sensitivity analysis is applied to prove the effectiveness and stability of this new method. PDF XML

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来源期刊

Informatica 工程技术-计算机：信息系统

CiteScore

5.90

自引率

6.90%

发文量

审稿时长

12 months

期刊介绍： The quarterly journal Informatica provides an international forum for high-quality original research and publishes papers on mathematical simulation and optimization, recognition and control, programming theory and systems, automation systems and elements. Informatica provides a multidisciplinary forum for scientists and engineers involved in research and design including experts who implement and manage information systems applications.