چکیده:
In this study, an evaluation model is developed to assess the credibility of the
loan applicants. The proposed model is a multicriteria decision making
(MCDM) problem consisting of numerous criteria by integrating analytic
hierarchy process (AHP) and genetic algorithm (GA). In the case of apparent
consensus for several measures, the research clearly indicates that both
quantitative and qualitative information must be employed in evaluating loan
applicants. The AHP approach is widely used for MCDM in various scopes. In
2008 Lin et al proposed the adaptive AHP approach (A3)in order to decrease
the number of steps for checking the inconsistency in the AHP model. The
study presents a MCDM model by developing the new adaptive AHP
approach (N_A3) already proposed by Herrera-Viedma in 2004. The proposed
model has led to fewer calculations, and less complexity. The model was
applied to 200 clients in order to show its efficiency and applicability. A brief
look at the implementation of the model showed that it is significantly valid in
selecting clients with respect to the known criteria, besides decision making
regarding the determination of the assessment factors.
خلاصه ماشینی:
"proposed the adaptive AHP approach (A3) method which used a soft computing scheme, Genetic Algorithm (GA), to recover the real number weightings of the various criteria in AHP and provided a function for automatically improving the consistency ratio of pair wise comparisons (Lin et al.
Additionally with proposed model, we can recover the real number weightings based on subjective and objective decision of the various criteria in A3 model and provide a function to improve automatically consistency ratio of pair wise comparisons and cover nonlinear relationships of PWM.
Formulate the GA for N_A3 3 Step1: Identification, classification and, 1 assessment of the critical factors and criteria and calculation of priority 2 Step2: Constructing N_A3 structure and calculating each criterion's weight (GLOBAL) 3 Step3: The hybrid expert system based on the decision-making rules and N_A3 results New client ACCEPT Yes Positive response No Is it improvabl Providing improvement initiatives for credit Yes Responses to three principal questions regarding applicants No Positive response Yes No REJECT Calculating each clients' score using N_A3 Determining the required level of resources Making the decision according to the defined rules in the expert system Fig 1.
1. Feature selection and Calculatin of each Criterion's weights In order to gain knowledge on the credit client assessment model, in the first step, several interviews are conducted in which the candidates are executive managers, and experts familiar with this context from several banks and financial organizations in Iran."