Cloud Model Based Genetic Algorithm and Its Applications

Traditional genetic algorithm(GA) easily gets stuck at a local optimum,and often has slow convergent speed.As a novel genetic algorithm,cloud-model-based genetic algorithm(CGA) was originally proposed.CGA is based on both the idea of GA and the properties of randomness and stable tendency of a normal cloud model.In this algorithm,a Y-conditional normal cloud generator is used as the cross operator of GA,and a basic normal cloud generator is used as the mutation operator.Finally,the experiments of function optimization and IIR digital filter design were conducted to compare CGA with standard GA,NQGA,CAGA and LARES.From the simulation results,it is believed that CGA is effective and will become a promising candidate of evolutionary algorithms.