Evidential Reasoning Approach for Multiattribute Decision Analysis Under Both Fuzzy and Interval Uncertainty

被引:65
作者
Guo, Min [1 ]
Yang, Jian-Bo [2 ,3 ]
Chin, Kwai-Sang [4 ]
Wang, Hong-Wei [1 ]
Liu, Xin-Bao [3 ]
机构
[1] Huazhong Univ Sci & Technol, Inst Syst Engn, Key Lab lmage Proc & Intelligent Control, Wuhan 430074, Peoples R China
[2] Univ Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
[3] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[4] City Univ Hong Kong, Dept Mfg Engn & Engn Management, Kowloon, Hong Kong, Peoples R China
基金
英国工程与自然科学研究理事会;
关键词
Fuzzy sets; multiple attribute decision analysis (MADA); evidential reasoning (ER) approach; uncertainty modeling; utility; BELIEF STRUCTURES; SETS; PROBABILITIES; AGGREGATION; SAFETY;
D O I
10.1109/TFUZZ.2008.928599
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
Many multiple attribute decision analysis (MADA) problems are characterized by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) and the interval grade ER (IER) approaches have been developed in recent years to support the solution of MADA problems with interval uncertainties and local ignorance in decision analysis. In this paper, the ER approach is enhanced to deal with both interval uncertainty and fuzzy beliefs in assessing alternatives on an attribute. In this newly developed fuzzy IER (FIER) approach, local ignorance and grade fuzziness are modeled under the integrated framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A numerical example is provided to illustrate the detailed implementation process of the FIER approach and its validity and applicability.
引用
收藏
页码:683 / 697
页数:15
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