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受生物免疫原理的启发而产生的人工免疫算法,是一种新型的随机启发式搜索算法。基于生物免疫系统机制,采用实数编码,利用分类变异替代传统的变异操作,提出了一种改进的用于多模态函数优化的免疫算法。算法包括免疫选择、分类变异、免疫记忆和免疫网络促进与抑制操作。文中详细讨论了算法的相关概念及算法步骤,通过对多模态测试函数进行仿真实验,实验结果表明了改进算法的有效性。
The artificial immune algorithm, inspired by the principle of biological immunity, is a new type of random heuristic search algorithm. Based on the mechanism of biological immune system, a real coding algorithm is used to replace the traditional mutation operation with classification mutation. An improved immune algorithm is proposed for multimodal function optimization. Algorithms include immune selection, taxonomic variation, immune memory and immune network facilitation and repression. In this paper, the related concepts and algorithm steps of the algorithm are discussed in detail. By simulating the multi-modal test function, the experimental results show the effectiveness of the improved algorithm.