A TODIM-Based Approach to Large-Scale Group Decision Making with Multi-Granular Unbalanced Linguistic Information

被引：0

作者：

Yu, Wen-Yu ^{[1
]}

Zhang, Zhen ^{[2
]}

Zhong, Qiu-Yan ^{[1
]}

机构：

[1] Dalian Univ Technol, Inst Informat Management & Informat Syst, Dalian, Peoples R China

[2] Dalian Univ Technol, Inst Syst Engn, Dalian, Peoples R China

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | 2017年

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

REPRESENTATION MODEL; TERM SETS; METHODOLOGY; PREFERENCES; EXPERTS; WORDS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Large-scale group decision making problems exist widely in human being's daily life. In this paper, a new approach to large-scale multi-attribute group decision making with multigranular unbalanced linguistic information is developed. First, an algorithm is proposed to represent the initial multi-granular unbalanced linguistic information of decision makers with the use of unbalanced linguistic distribution assessments. Based on the gain and loss of an unbalanced linguistic distribution assessment over another, the classical TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method is then extended to derive a raking of alternatives for largescale multi-attribute group decision making problems. Finally, an example for talent selection is used to demonstrate the feasibility of the proposed approach.

引用

页数：6

共 28 条

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