文献类型：期刊文献

英文题名：On a Simple and Efficient Approach to Probability Distribution Function Aggregation

作者：Cai, Mengya[1];Lin, Yingzi[2];Han, Bin[3];Liu, Changjun[1];Zhang, Wenjun[1,4]

机构：[1]East China Univ Sci & Technol, Complex & Intelligent Syst Res Ctr, Shanghai 200237, Peoples R China;[2]Northeastern Univ, Dept Mech & Ind Engn, IHMS Lab, Boston, MA 02115 USA;[3]Univ Saskatchewan, Dept Biomed Engn, Saskatoon, SK S7N 5A9, Canada;[4]Univ Saskatchewan, Dept Mech Engn, Saskatoon, SK S7N 5A9, Canada

年份：2017

卷号：47

期号：9

起止页码：2444

外文期刊名：IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

收录：;EI(收录号：20173804190674);WOS:【SSCI(收录号:WOS:000411097600002)，SCI-EXPANDED(收录号:WOS:000411097600002)】；

基金：This work was supported in part by the China Scholarship Council, and in part by the ECUST Central University Grant.

语种：英文

外文关键词：Aggregation; group judgment; linear feedback iteration; probability distribution

摘要：In group decision making, it is inevitable that the individual decision maker's subjectivity is involved, which causes difficulty in reaching a group decision. One of the difficulties is to aggregate a small set of expert opinions with the individual subjectivity or uncertainty modeled with probability theory. This difficult problem is called probability distribution function aggregation (DFA). This paper presents a simple and efficient approach to the DFA problem. The main idea of the proposed approach is that the DFA problem is modeled as a nonlinear function of a set of probability distribution functions, and then a linear feedback iteration scheme is proposed to solve the nonlinear function, leading to a group judgment or decision. Illustration of this new approach is given by a well-known DFA example which was solved with the Delphi method. The DFA problem is a part of the group decision problem. Therefore, the proposed algorithm is also useful to the decision making problem in general. Another contribution of the this paper is the proposed notation of systematically representing the imprecise group decision problem with the classification of imprecise information into three classes, namely incomplete information, vague information, and uncertain information. The particular DFA problem dealt with in this paper is then characterized with this general notation.