一种改进的自适应免疫遗传算法

An Improved Adaptive Immune Genetic Algorithm

为了解决免疫遗传算法(IGA)存在的“停滞”问题和“早熟”问题,提出了一种改进的自适应免疫遗传算法(IAIGA)。首先通过在IGA中加入疫苗动态自适应提取策略以及交叉和变异操作的自适应策略对其进行改进,然后分别采用IGA和IAIGA对6组基准函数进行了寻优仿真实验,比较了两种算法在搜索全局最优解、优化精度和收敛速度上的差别,最终结果表明,IAIGA可解决IGA存在的“早熟”和“停滞”问题,收敛速度更快,收敛稳定性更好,寻优精度更高。

In order to solve the"premature"and"stagnation"problems of the immune genetic algorithm(IGA),an improved adaptive immune genetic algorithm(IAIGA)is proposed in this paper.Firstly,it is improved by adding the adaptive strategy of crossover and mutation operation and the dynamic adaptive extraction strategy of vaccine to the IGA.Then,IGA and IAIGA are used to optimize the 6 groups of benchmark functions,and the differences between the two algorithms in searching for the global optimal solution,optimization accuracy and convergence speed are compared.The results show that IAIGA could solve the"prematurity"and"stagnation"problems of IGA,with faster convergence speed,better convergence stability and higher optimization precision.