利用免疫系统的克隆选择机制,提出一种用于函数优化的算法. 算法的主要特点是:在迭代过程中,不仅抗体得到进化,同时建立变异向量集,令变异向量同步进化,协同工作,达到优化的目的. 仿真实验表明,所提出的算法能以较快的速度完成给定范围的搜索和全局优化任务-By using the clonal selection echanism of the immune system , a method for function optimizing is proposed. The character of this algorithm is not only the antibodies evolution , but also a mutation vectors set is built

for cooperative co2evolution to breed and reproduce successful mutation steps. The simulation result s show that this algorithm can converge to the global optimum at quicker rate in a given range.