An Immune Genetic Algorithm Based on Chaos Theory
基于混沌理论的免疫遗传算法

To increase operating efficiency of immune genetic algorithm, a chaos immune genetic algorithm is presented based on the chaotic character of the immune system. The over-spread character of the chaos sequence was used to overcome redundancies, and the chaos initial value sensitivity was used to enlarge the searching space. Thus, the diversity of population was retained and the local optimization was avoided. The experimental results show that the chaos immune genetic algorithm evidently improves the convergent speed and astringency.