基于优秀基因传播的免疫优化算法

对文献[5]的工作进行改进，改进基因重组策略，增加免疫基因传播操作，使得算法能够更快更好的搜索最优解．核心思想是区分成熟抗体中高层次抗体和低层次抗体，低层次群体不断更新，高层次群体相对稳定，但不断从低层次群体中学习优秀基因完善自身．本文详细介绍了该算法的设计思想和具体实验，实验结果说明本算法具有较好的问题求解能力．

Immune Optimization Algorithm Based on Excellent Gene Spreading

In this paper Gene Spreading operation and improving gene recombination are introduced to extend the work in literature[5], so that better solution could be searched more quickly. The key idea is to distinguish high-level antibodies between low-level antibodies. Low-level antibodies are generated and updated continuously while high-level antibodies keep relatively stable with learning excellent gene from low-level antibodies. Such motivation and design are introduced in detail in this paper. The experiment results prove that our algorithm has a quick and good ability of problem solving.