多模态函数优化的免疫算法

Immune algorithm for multi modal function optimization

模拟抗体搜索机制,结合免疫网络理论,提出一种新的优化算法.该算法用抗体表示函数优化解的可能模式,通过构造克隆选择算子完成全局和局部最优解的搜索,利用B细胞网络保持多种抗体并存.典型函数优化测试结果表明,该算法能够较好地实现全局最优解和局部最优解的同步搜索和保持,具有较强的多模态函数优化能力.

By simulating the antibody search mechanism, and combining the immune network theory, a new immune learning algorithm for multi-modal function optimization was presented. In this algorithm, antibodies represented the possible optimization solutions of functions. Cloning operator was used to search the local optima and the global optimum. B cell network was formed to maintain the diverse antibodies. Testing results of typical multi-modal function optimization show its effectiveness.