An Intelligent-Agent-Based Multicriteria Fuzzy Group Decision Making Model for Credit Risk Analysis

2008 ◽  
pp. 197-222 ◽  
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Credit Risk ◽  
Group Decision Making ◽  
Group Decision ◽  
Intelligent Agent ◽  
Agent Based ◽  
Credit Risk Analysis ◽  
Decision Making Model ◽  
Fuzzy Group Decision Making

scholarly journals Group decision-making using improved multi-criteria decision making methods for credit risk analysis

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 4135-4150 ◽  
Author(s):  
Wenshuai Wu ◽  
Gang Kou ◽  
Yi Peng
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Credit Risk ◽  
Group Decision Making ◽  
Group Decision ◽  
Ideal Solution ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Credit Risk Analysis ◽  
Grey Relational

Credit risk analysis is a core research issue in the field of financial risk management. This paper first investigates the analytic hierarchy process (AHP) as a method of measuring index weights for group decision-making (GDM). AHP for group decision-making (AHP-GDM) is then researched and applied, taking into full account the cognitive levels of different experts. Second, the concept of grey relational degree is introduced into the ideal solution of the technique for order of preference by similarity to ideal solution (TOPSIS). This concept fully considers the relative closeness of grey relational degree between alternatives and the ?ideal? solution in order to strengthen their relationship. The AHP-GDM method overcomes the problem of subjectivity in measuring index weights, and the revised TOPSIS (R-TOPSIS) method heightens the effectiveness of assessment results. An illustrative case using data from Chinese listed commercial banks shows that the R-TOPSIS method is more effective than both TOPSIS and grey relational analysis (GRA) in credit risk evaluation. The two improved multi-criteria decision making (MCDM) methods are also applied to empirical research regarding the credit risk analysis of Chinese urban commercial banks. The results indicate the validity and effectiveness of both methods.

A Variable Precision Fuzzy Rough Group Decision-Making Model for IT Offshore Outsourcing Risk Evaluation

2010 ◽  
pp. 2113-2129
Author(s):  
Guodong Cong ◽  
Jinlong Zhang ◽  
Tao Chen ◽  
Kin-Keung Lai
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Risk Evaluation ◽  
Group Decision ◽  
Offshore Outsourcing ◽  
Variable Precision ◽  
Rough Group ◽  
Fairness And Efficiency ◽  
Decision Making Model ◽  
Fuzzy Group Decision Making

Risks evaluation is critical for the success of IT offshore outsourcing. Based on fuzzy group decision-making (FGDM) and variable precision fuzzy rough set (VPFRS), this article proposes a new integrated model, variable precision fuzzy rough group decision-making (VPFRGDM), to evaluate the risk in IT offshore outsourcing. This model can improve the capability to handle potential errors fairness and efficiency of risk evaluation, and is verified by a numerical case.

FUZZY GROUP DECISION MAKING MODEL BASED ON CREDIBILITY THEORY AND GRAY RELATIVE DEGREE

2009 ◽  
Vol 08 (03) ◽  
pp. 515-527 ◽  
Author(s):  
CONGJUN RAO ◽  
JIN PENG
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Relative Degree ◽  
Credibility Theory ◽  
New Model ◽  
Trapezoidal Fuzzy Numbers ◽  
Decision Making Model ◽  
Fuzzy Group Decision Making

In this paper, the problems of fuzzy multi-attribute group decision making in which the attribute values are given in the form of linguistic fuzzy numbers are studied. First of all, a new method called fuzzy dominance is given for ranking trapezoidal fuzzy numbers based on the credibility theory. Then the TOWA operator is presented to aggregate the trapezoidal fuzzy numbers. Furthermore, a new model is presented for the problems of fuzzy multi-attribute group decision making via TOWA operator, fuzzy dominance method and gray relative degree. Finally, a decision-making example is given to demonstrate the feasibility and rationality of this new model.

Sign in / Sign up

Export Citation Format

Share Document