重用抗体优良片断的免疫进化算法

基于克隆选择原理与算法,通过分析具体现象阐述了改进克隆选择算法的思想来源,设计了挖掘抗体中优秀决定基因并生成记忆集、封装优秀决定基片段、用变异抗体群中亲和度高的抗体按概率替换记忆抗体群中低亲和度抗体的方法，获得了重用抗体优良片断的克隆选择算法.借鉴强度Pareto进化算法的进化框架,提出了重用抗体优良片断的免疫进化算法.该算法通过克隆选择替代选择、交叉、重组等遗传操作.在一组0/1背包问题上的测试结果表明,所提出的算法可以有效保持种群多样性,获得较高质量的Pareto非劣解集.

Immune Evolutionary Algorithm Reusing Excellent Genes of Antibody

By expounding the ideological origin of improving the clonal selection algorithm through the analysis of the specific phenomenon,the method to extract excellent gene schema to fill a memory pool from antibody set,to package excellent gene segment,and to replace low affinity antibody with high affinity antibody with probability from mutation antibody population during updating memory antibody population was designed based on clonal selection principle and algorithm,and then an improved clonal selection algorithm reusing excellent gene segment was put forward.Refering to the framework of strength Pareto evolutionary algorithm,the immune evolutionary algorithm reusing excellent genes of antibody(RG-IEM) was proposed,which implements the genetic operation such as selection,crossover and recombinant by applying the improved clonal selection algorithm.Taking a series of multi-objective 0/1 knapsack problems to check RG-IEA’s performance,the results show that RG-IEA is capable of maintaining the diversity of population and obtaining solutions approximating to Pareto front.