管理工程学报2012，Vol.26Issue(2)：94-100,7.
基于证据推理的不确定多属性决策方法
Evidential Reasoning-Based Approach for Multiple Attribute Decision Making Problems under Uncertainty
摘要
Abstract
The previous study shows that the evidential reasoning algorithm is an effective and rational method to solve MADM (Multiple Attribute Decision Making) problems under uncertainty. However, the method has constraints that attribute weights should be deterministic and evaluation grades assessing basic attributes and general attributes should be consistent. However, these constraints are not relevant to the actual decision-making problems, especially for basic qualitative attributes. Existing subjective and objective methods have defect for basic attribute weights. Most methods assume that the grade is the same in order to evaluate grades based on basic and general attributes. Therefore, these methods are not effective to assist the decision making process and solve problems.In consideration of the weakness of previous study, this study proposes a method based on the evidential reasoning for MADM under uncertainty with the goal of extending evidential reasoning algorithm into a more general decision environment.The first part is to determine basic attribute weights. We first briefly introduce the evidential reasoning algorithm, discussing two major issues related to its effective application for MADM under uncertainty: (1) how to totally determine basic attribute weights, and (2) how to fully implement the transformation of distributed assessment from basic attributes into general attributes. In addition, we calculate basic attribute weights using the information entropy of decision matrix to solve the first problem. In the second part, we implement the equivalent transformation of distributed assessments from basic attributes into general attributes by assuming that evaluation grades assessing basic attributes and general attributes are not the same.We first fuzz the distributed assessments of basic attributes according to different data types of basic attribute values, and then implement, based on fuzzy transformation theory, the unified form of general distributed assessments by combination of fuzzy distributed assessments of basic attributes with fuzzy relation between evaluation grades assessing basic attributes and general attributes, the second problem solved. Finally, we apply the evidential reasoning algorithm to rank all alternatives. An illustrative example is employed to examine the feasibility and validity of decision-making results based on the present approach.In summary, the evidential reasoning algorithm essentially establishes a nonlinear relationship between an aggregated assessment for a general attribute and an original assessment for basic attributes. The algorithm is still an effective and rational method to solve MADM problems under uncertainty and in an ideal environment. In this paper, we successfully tackle primary issues of the evidential reasoning algorithm that can be extended from an ideal decision environment into a more general decision environment so that the algorithm can resolve more sophisticated decision-making problems.关键词
证据推理/多属性决策/信息熵/模糊变换Key words
evidential reasoning/ multiple attribute decision making/ information entropy/ fuzzy transformation分类
管理科学引用本文复制引用
郭凯红,李文立..基于证据推理的不确定多属性决策方法[J].管理工程学报,2012,26(2):94-100,7.基金项目
国家自然科学基金资助项目(70972058) （70972058）
国家自然科学基金重大资助项目(70890083) （70890083）
教育部社科研究青年基金资助项目(10YJC630063) （10YJC630063）
