Generalized hesitant fuzzy sets and their application in decision support system

被引:227
作者
Qian, Gang [1 ]
Wang, Hai [1 ]
Feng, Xiangqian [1 ,2 ]
机构
[1] Nanjing Normal Univ, Dept Management Sci & Engn, Nanjing, Jiangsu, Peoples R China
[2] Jiangsu Res Ctr Informat Secur & Privacy Technol, Nanjing, Jiangsu, Peoples R China
关键词
Group decision making; Multi criteria decision making; Hesitant fuzzy sets; Intuitionistic fuzzy sets; Aggregation operator; Decision support system; AGGREGATION OPERATORS; VAGUE SETS; INFORMATION;
D O I
10.1016/j.knosys.2012.08.019
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hesitant fuzzy sets are very useful to deal with group decision making problems when experts have a hesitation among several possible memberships for an element to a set. During the evaluating process in practice, however, these possible memberships may be not only crisp values in [0,1], but also interval values. In this study, we extend hesitant fuzzy sets by intuitionistic fuzzy sets and refer to them as generalized hesitant fuzzy sets. Zadeh's fuzzy sets, intuitionistic fuzzy sets and hesitant fuzzy sets are special cases of the new fuzzy sets. We redefine some basic operations of generalized hesitant fuzzy sets, which are consistent with those of hesitant fuzzy sets. Some arithmetic operations and relationships among them are discussed as well. We further introduce the comparison law to distinguish two generalized hesitant fuzzy sets according to score function and consistency function. Besides, the proposed extension principle enables decision makers to employ aggregation operators of intuitionistic fuzzy sets to aggregate a set of generalized hesitant fuzzy sets for decision making. The rationality of applying the proposed techniques is clarified by a practical example. At last, the proposed techniques are devoted to a decision support system. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:357 / 365
页数:9
相关论文
共 41 条
[1]  
Alonso S, 2008, J MULT-VALUED LOG S, V14, P371
[2]   INTUITIONISTIC FUZZY-SETS [J].
ATANASSOV, KT .
FUZZY SETS AND SYSTEMS, 1986, 20 (01) :87-96
[3]   Improved hierarchical fuzzy TOPSIS for road safety performance evaluation [J].
Bao, Qiong ;
Ruan, Da ;
Shen, Yongjun ;
Hermans, Elke ;
Janssens, Davy .
KNOWLEDGE-BASED SYSTEMS, 2012, 32 :84-90
[4]   On averaging operators for Atanassov's intuitionistic fuzzy sets [J].
Beliakov, G. ;
Bustince, H. ;
Goswami, D. P. ;
Mukherjee, U. K. ;
Pal, N. R. .
INFORMATION SCIENCES, 2011, 181 (06) :1116-1124
[5]   Vague sets are intuitionistic fuzzy sets [J].
Bustince, H ;
Burillo, P .
FUZZY SETS AND SYSTEMS, 1996, 79 (03) :403-405
[6]   Developing a group decision support system based on fuzzy information axiom [J].
Cebi, Selcuk ;
Kahraman, Cengiz .
KNOWLEDGE-BASED SYSTEMS, 2010, 23 (01) :3-16
[7]   HANDLING MULTICRITERIA FUZZY DECISION-MAKING PROBLEMS BASED ON VAGUE SET-THEORY [J].
CHEN, SM ;
TAN, JM .
FUZZY SETS AND SYSTEMS, 1994, 67 (02) :163-172
[8]  
Chen T.-Y., 2008, P 11 JOINT C INF SCI
[9]   Optimistic and pessimistic decision making with dissonance reduction using interval-valued fuzzy sets [J].
Chen, Ting-Yu .
INFORMATION SCIENCES, 2011, 181 (03) :479-502
[10]   MISMIS - A comprehensive decision support system for stock market investment [J].
Cho, Vincent .
KNOWLEDGE-BASED SYSTEMS, 2010, 23 (06) :626-633