Chaos genetic algorithm and its application in test generation
Kang Bo · Systems engineering and electronics · 2006
To consider the problem of premature and slow convergence in standard genetic algorithm,a novel chaos genetic algorithm is proposed.In the algorithm,crossover and mutation operation is controlled respectively by a chaotic sequence which is stochastic,ergodic and regular.Furthermore,a neural network model for combinatorial circuit test generation is introduced.Based on the model,a test generation approach with chaos genetic algorithm is discussed in detail.The experimental results demonstrate that the proposed approach surmounts effectively the local convergence problem of standard genetic algorithm and improves the test generation speed.