【摘要】 将免疫算法、混沌与遗传算法相结合,提出了一种新颖的混沌免疫遗传算法,该方法利用混沌运动的遍历性、随机性来产生初始种群,加快搜索的速度;利用免疫原理的浓度计算及调整加入新的混沌序列来补充种群,增加种群的多样性避免陷入局部最优;交叉变异结束后在最优解附近再用混沌进行局部寻优提高解的精度。实验结果表明,所提出的算法能寻找到更好的优化结果,并且在搜索速度上明显优于遗传和免疫遗传算法。更多还原

【Abstract】 We present a novel algorithm which combines immune algorithm、chaos and genetic algorithm.This immune genetic algorithm based on chaos initializes cluster by the over-spread character and randomicity of chaos to improve search speed and renews cluster by chaos sequence and enhancing cluster diversity to avoid local optimization.Chaos also is adopts to optimize the local optimization to increase precision.The experiment results show the immune genetic based on chaos truth can search the optimization,and have an good convergent speed.更多还原