基于高频变异免疫进化算法的多峰值函数优化

多峰值函数优化问题一直是数值优化领域中研究的难点。本文提出一种基于高频变异的改进免疫进化算法，通过克隆选择高频变异抗体来增加群体多样性，又赋予抗体生命期抑制群体暴增，此外引入变异因子提高抗体识别抗原的速度。该算法即克服克隆选择算法的收敛速度慢，又克服遗传算法易陷入局部最优解的不足。对三个多峰值函数优化仿真，并和标准遗传算法、改进遗传算法和佳点遗传算法的计算结果进行比较，证明该方法可以快速收敛到全局最优解。

Multi-modal Function Optimization Based on Immune Evolutionary Algorithm with High Frequency Variation

The problem of multi-modal function optimization has been a difficulty in the field of numerical optimization.An improved immune evolutionary algorithm based on high frequency variation was proposed that the clonal expansion was applied to increase population diversity,the life span of antibody was given to suppress population explosion and the mutation factor was introduced to improve the speed of antibodies recognizing antigens.This algorithm could overcome the shortages of other algorithms that the clona...