Genetic algorithm with forgetting and its application in initial credit scoring

Based on the forgetting strategy,an improved genetic algorithm was proposed to solve the problem of local optimization,and a forgetting operator as well as its forgetting probability was given.For the search space was increased by forgetting some genes during the period of inheritance,the algorithm can break away from local optimization and avoid the premature convergence to the greatest extent.By using the algorithm to deal with the credit scoring of telecom customers for different arrears rates,the optimum solution of credit weights in the case of high rate of arrears was found,so it solves the problem that the fitness of credit weights is low for the credit scoring of telecom customers in high arrears rates.Experimental results demonstrate that the algorithm is effective and feasible.Compared with the standard genetic algorithm,the proposed algorithm can obtain better quality results.