成果信息
Managing Multigranular Linguistic Distribution Assessments in Large-Scale Multiattribute Group Decision Making
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在榜期数::ESI高被引论文(2018年第4期);
文献类型:期刊论文
标题:Managing Multigranular Linguistic Distribution Assessments in Large-Scale Multiattribute Group Decision Making
作者:Zhang, Zhen[1];Guo, Chonghui[1];Martinez, Luis[2]
机构:
[1]Dalian Univ Technol, Inst Syst Engn, Dalian 116024, Peoples R China.;
[2]Univ Jaen, Dept Comp Sci, Jaen 23071, Spain.;
通讯作者:Zhang, Z (reprint author), Dalian Univ Technol, Inst Syst Engn, Dalian 116024, Peoples R China.
来源信息:年:2017  卷:47  期:11  页码范围:3063-3076  
期刊信息:IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS影响因子和分区  ISSN:2168-2216
增刊:正刊
学科:工程学
收录情况:SCIE(WOS:000413071700023)  EI(20174904487504)  SSCI(WOS:000413071700023)  
所属部门:管理与经济学部
重要成果类型:ESI高被引
语言:外文
发表时间:2017-11-01
全文链接:DOI百度学术
被引频次:21
人气指数:433
浏览次数:433
基金:National Natural Science Foundation of China [71501023, 71171030, 61463039]; Funds for Creative Research Groups of China [71421001]; China Post-Doctoral Science Foundation [2015M570248]; Fundamental Research Funds for the Central Universities [DUT15RC(3)003]; FEDER; [TIN2015-66524-P]
关键词:Group decision making (GDM); large-scale GDM (LGDM); linguistic distribution assessment; multigranular linguistic information
摘要:Linguistic large-scale group decision making (LGDM) problems are more and more common nowadays. In such problems a large group of decision makers are involved in the decision process and elicit linguistic information that are usually assessed in different linguistic scales with diverse granularity because of decision makers' distinct knowledge and background. To keep maximum information in initial stages of the linguistic LGDM problems, the use of multigranular linguistic distribution assessments seems a suitable choice, however, to manage such multigranular linguistic distribution assessments, it is necessary the development of a new linguistic computational approach. In this paper, it is proposed a novel computational model based on the use of extended linguistic hierarchies, which not only can be used to operate with multigranular linguistic distribution assessments but also can provide interpretable linguistic results to decision makers. Based on this new linguistic computational model, an approach to linguistic large-scale multiattribute group decision making is proposed and applied to a talent selection process in universities.
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