A Genetic Algorithm Based on Immune and Chaos

An immune chaos genetic algorithm is presented to keep population´s diversity, avoid local optimum and improve performance of genetic algorithm. Immune selection is used to adjust antibody´s density, and the advantage of individuals is exerted by introducing vaccination. By virtue of the over-spread character of chaos sequence, it is used to generate the pool of antibody to overcome redundancies. At the same time, searching space is enlarged by using sensitivity of chaos initial value. The result of simulation experiments shows that the algorithm has good performance in the aspects of both the convergence speed and the global optimum.