On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
复制标题
DOI：
10.1109/tsmca.2002.802746
复制
发表时间：
2002-05-01
影响因子：
--
通讯作者：
Xu, DL
中科院分区：
文献类型：
--
作者：
Yang, JB;Xu, DL
在多属性决策分析（MADA）中，人们通常需要处理具有不确定性的数值数据和定性信息。正确表示和使用不确定信息来进行理性决策分析至关重要。基于多级评估框架，开发了一种支持此类决策分析的证据推理（ER）方法，其核心是在该框架和Dempster-Shafer（D-S）理论的证据组合规则的基础上开发的ER算法。办法有。已应用于工程设计选择、组织自我评估安全和风险评估以及供应商评估。本文研究了ER方法的基本特征。提出了权重归一化和基本概率分配的新方案。最初的 ER 方法是。进一步发展以增强不确定性属性的聚合过程。提出效用区间来描述无知对决策分析的影响。探索了新 ER 方法的几个特性，奠定了 ER 方法的理论基础。使用 ER 方法检查摩托车评估问题的数值示例。提供计算步骤和分析结果以演示其实现过程。
In multiple attribute decision analysis (MADA), one often needs to deal with both numerical data and qualitative information with uncertainty. It is essential to properly represent and use uncertain information to conduct rational decision analysis. Based on a multilevel evaluation framework, an evidential reasoning (ER) approach has been developed for supporting such decision analysis, the kernel of which is an ER algorithm developed on the basis of the framework and the evidence combination rule of the Dempster-Shafer (D-S) theory. The approach has. been applied to engineering design selection, organizational self-assessment safety and risk assessment, and supplier assessment.In this paper, the fundamental features of the ER approach are investigated. New schemes for weight normalization and basic probability assignments are proposed. The original ER approach is. further developed to enhance the process of aggregating attributes with uncertainty. Utility intervals are proposed to describe the impact of ignorance on decision analysis. Several properties of the new ER approach are explored, which lay the theoretical foundation of the ER approach. A numerical example of a motorcycle evaluation problem is examined using the ER approach. Computation steps and analysis results are provided in order to demonstrate its implementation process.