The group consensus based evidential reasoning approach for multiple attributive group decision analysis

被引:106
作者
Fu, Chao [1 ]
Yang, Shan-Lin
机构
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Decision analysis; Multiple attributive group decision analysis; Evidential reasoning approach; Group consensus; Compatibility measure; FUZZY PREFERENCE RELATIONS; LINGUISTIC ASSESSMENTS; MAKING PROBLEMS; MODEL; UNCERTAINTY; INFORMATION; CONSISTENCY; SYSTEM; AGGREGATION; SELECTION;
D O I
10.1016/j.ejor.2010.03.011
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Many multiple attribute decision analysis problems include both quantitative and qualitative attributes with various kinds of uncertainties such as ignorance, fuzziness, interval data, and interval belief degrees. An evidential reasoning (ER) approach developed in the 1990s and in recent years can be used to model these problems. In this paper, the ER approach is extended to group consensus (GC) situations for multiple attributive group decision analysis problems. In order to construct and check the GC, a compatibility measure between two belief structures is developed first. Considering two experts' utilities, the compatibility between their assessments is naturally constructed using the compatibility measure. Based on the compatibility between two experts' assessments, the GC at a specific level that may be the attribute level, the alternative level, or the global level, can be constructed and reached after the group analysis and discussion within specified times. Under the condition of GC, we conduct a study on the forming of group assessments for alternatives, the achievement of the aggregated utilities of assessment grades, and the properties and procedure of the extended ER approach. An engineering project management software selection problem is solved by the extended ER approach to demonstrate its detailed implementation process, and its validity and applicability. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:601 / 608
页数:8
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