文献类型：期刊文献

英文题名：A semantic model for computing with flexible linguistic expressions and the application in MCGDM

作者：Jiang, Le[1];Liu, Hongbin[2];Cui, Ning[1]

第一作者：Jiang, Le

通讯作者：Liu, HB[1]

机构：[1]Zhengzhou Univ Light Ind, Sch Math & Informat Sci, Zhengzhou 450000, Henan, Peoples R China;[2]Henan Univ Econ & Law, Sch Math & Informat Sci, Zhengzhou 450046, Henan, Peoples R China

第一机构：Zhengzhou Univ Light Ind, Sch Math & Informat Sci, Zhengzhou 450000, Henan, Peoples R China

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Sch Math & Informat Sci, Zhengzhou 450046, Henan, Peoples R China.|[1048425]河南财经政法大学数学与信息科学学院;[10484]河南财经政法大学;

年份：2021

卷号：158

外文期刊名：COMPUTERS & INDUSTRIAL ENGINEERING

收录：;EI(收录号：20212610572047);Scopus(收录号：2-s2.0-85108709658);WOS:【SCI-EXPANDED(收录号:WOS:000667165200032)】；

基金：We would like to thank the anonymous reviewers for their suggestions to improve the paper. This work is supported by the Arts & Social Science Research Funds of the Education Department of Henan Province (2020-ZDJH-022), and the National Natural Science Foundation of China (11701524, 11872175, 61803144).

语种：英文

外文关键词：Multi-criteria group decision making; Flexible linguistic expression; Triangular fuzzy number; Consensus reaching process; Autonomous driving

摘要：The flexible linguistic expression (FLE) is a generalization of the hesitant fuzzy linguistic term set and linguistic distribution. An FLE expresses a preference in the form of hesitant fuzzy linguistic term sets with the symbolic proportions. The existing studies mainly utilize a symbolic way to compute with FLEs. To provide a semantic model for computing with FLEs, this paper proposes to represent an FLE with a triangular fuzzy number. Two approaches based on the maximum entropy principle are introduced to compute the triangular fuzzy membership functions for complete and incomplete FLEs. A multi-criteria group decision making (MCGDM) model based on FLEs is then proposed, in which the criteria are divided into different subsets of sub-criteria which are selected for different decision makers. A consensus reaching process is introduced to improve consensus of the decision makers by modifying weights of the sub-criteria. Finally the MCGDM model is applied to an autonomous driving evaluation problem.