Multicriteria group decision making under incomplete preference judgments: Using fuzzy logic with a linguistic quantifier

被引:11
作者
Choi, Duke Hyun
Ahn, Byeong Seok
Kim, Soung Hie
机构
[1] Korea Adv Inst Sci & Technol, Grad Sch Management, Seoul 130722, South Korea
[2] Chung Ang Univ, Coll Business Adm, Seoul 156756, South Korea
[3] Korea Adv Inst Sci & Technol, Grad Sch Management, Seoul 130722, South Korea
关键词
D O I
10.1002/int.20218
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the face of increasing global competition and complexity of the socioeconomic environment, many organizations employ groups in decision making. Inexact or vague preferences have been discussed in the decision-making literature with a view to relaxing the burden of preference specifications imposed on the decision makers and thus taking into account the vagueness of human judgment. In this article, we present a multiperson decision-making method using fuzzy logic with a linguistic quantifier when each group member specifies incomplete judgment possibly both in terms of the evaluation of the performance of different alternatives with respect to multiple criteria and on the criteria themselves. Allowing for incomplete judgment in the model, however, makes a clear selection of the best alternative by the group more difficult. So, further interactions with the decision makers may proceed to the extent to compensate for the initial comfort of preference specifications. These interactions, however, may not guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfactory solution by the use of a linguistic-quantifier-guided aggregation that implies the fuzzy majority. This is an approach that combines a prescriptive decision method via mathematical programming and a well-established approximate solution method to aggregate multiple objects. (c) 2007 Wiley Periodicals, Inc.
引用
收藏
页码:641 / 660
页数:20
相关论文
共 44 条
[1]   Multiattribute decision aid with extended ISMAUT [J].
Ahn, BS .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2006, 36 (03) :507-520
[2]   Extending Malakooti's model for ranking multicriteria alternatives with preference strength and partial information [J].
Ahn, BS .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2003, 33 (03) :281-287
[3]  
[Anonymous], 1982, Judgement under Uncertainty: Heuristics and Biases
[4]   Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations [J].
Chiclana, F ;
Herrera, F ;
Herrera-Viedma, E .
FUZZY SETS AND SYSTEMS, 2001, 122 (02) :277-291
[5]   Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations [J].
Chiclana, F ;
Herrera, F ;
Herrera-Viedma, E .
FUZZY SETS AND SYSTEMS, 1998, 97 (01) :33-48
[6]  
Chiclana F., 1997, J FUZZY MATH, V4, P801
[7]  
Chun-Chin Wei, 2004, International Journal of Project Management, V22, P161, DOI 10.1016/S0263-7863(02)00064-9
[8]   A MULTIPLE CRITERIA DECISION-MODEL WITH ORDINAL PREFERENCE DATA [J].
COOK, WD ;
KRESS, M .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1991, 54 (02) :191-198
[9]   On the issue of obtaining OWA operator weights [J].
Filev, D ;
Yager, RR .
FUZZY SETS AND SYSTEMS, 1998, 94 (02) :157-169
[10]   Interactive group decision-making procedure using weak strength of preference [J].
Han, CH ;
Ahn, BS .
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2005, 56 (10) :1204-1212