Hesitant fuzzy linguistic entropy and cross-entropy measures and alternative queuing method for multiple criteria decision making

被引:215
作者
Gou, Xunjie [1 ]
Xu, Zeshui [1 ]
Liao, Huchang [1 ]
机构
[1] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Multiple criteria decision making; Hesitant fuzzy linguistic term set; Entropy measures; Cross-entropy measures; Weight-determining method; Alternative queuing method; TERM SETS; PREFERENCE RELATIONS; CONSISTENCY MEASURES; AGGREGATION; ENVIRONMENT; SIMILARITY;
D O I
10.1016/j.ins.2017.01.033
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hesitant fuzzy linguistic term set (HFLTS) is a useful tool for describing people's subjective cognitions in the process of decision making. Multiple criteria decision making (MCDM) involves two important steps: (1) determining the criteria weights; (2) obtaining a suitable ranking of alternatives. In this paper, we propose some hesitant fuzzy linguistic entropy and cross-entropy measures, and then establish a model for determining the criteria weights, which considers both the individual effect of each hesitant fuzzy linguistic element (HFLE) and the interactive effect between any two HFLEs with respect to each criterion. Additionally, we give a hesitant fuzzy linguistic alternative queuing method (HFL-AQM) to deal with the MCDM problems. The directed graph and the precedence relationship matrix make the calculation processes and the final results much more intuitive. Finally, a case study concerning the tertiary hospital management is made to verify the weight-determining method and the HFL-AQM. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:225 / 246
页数:22
相关论文
共 53 条
[1]   The development of granular rule-based systems: a study in structural model compression [J].
Ahmad S.S.S. ;
Pedrycz W. .
Granular Computing, 2017, 2 (01) :1-12
[2]   A neurofuzzy algorithm for learning from complex granules [J].
Apolloni, Bruno ;
Bassis, Simone ;
Rota, Jacopo ;
Galliani, Gian Luca ;
Gioia, Matteo ;
Ferrari, Luca .
GRANULAR COMPUTING, 2016, 1 (04) :225-246
[3]   INTUITIONISTIC FUZZY-SETS [J].
ATANASSOV, KT .
FUZZY SETS AND SYSTEMS, 1986, 20 (01) :87-96
[4]   TOPSIS for Hesitant Fuzzy Linguistic Term Sets [J].
Beg, Ismat ;
Rashid, Tabasam .
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2013, 28 (12) :1162-1171
[5]   Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems [J].
Chen, Na ;
Xu, Zeshui .
INFORMATION SCIENCES, 2015, 292 :175-197
[6]   Multicriteria linguistic decision making based on hesitant fuzzy linguistic term sets and the aggregation of fuzzy sets [J].
Chen, Shyi-Ming ;
Hong, Jia-An .
INFORMATION SCIENCES, 2014, 286 :63-74
[7]   Orthopairs and granular computing [J].
Ciucci, Davide .
GRANULAR COMPUTING, 2016, 1 (03) :159-170
[8]   Bridging gaps between several forms of granular computing [J].
Dubois, Didier ;
Prade, Henri .
GRANULAR COMPUTING, 2016, 1 (02) :115-126
[9]  
Estrella FJ, 2015, ADV INTEL SYS RES, V89, P799
[10]   Some new fuzzy entropy formulas [J].
Fan, JL ;
Ma, YL .
FUZZY SETS AND SYSTEMS, 2002, 128 (02) :277-284