基于相似性矢量距的免疫遗传算法在函数寻优中的应用

The Application of IGA(Immune Genetic Algorithm) Based on the Similarity and Vector Distance in the Function Optimization

在分析人工免疫算法的基础上,采用了基于相似性矢量距的免疫遗传算法,介绍了该算法的基本步骤及特点,并通过对Ackley测试函数性能分析实验,对所采用算法的优化性能进行了分析与验证。结果表明该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,较标准遗传算法具有更强的全局搜索能力。

Based on analyzing the artificial immune algorithm, this paper adopts the IGA based on the similarity and vector distance, introduces some basic procedures and characteristics of this algorithm, and through the analysis and test on the performances of Ackley function, makes the analysis and certification of the optimized performances of the adopted algorithm. The results show that the algorithm can fulfill the search and the global optimum at a quicker rate in a given range compared with the typical genetic algorithm.