基于全局粒子群的协作型人工免疫网络优化算法

Global Particle Swarm Based Cooperative Artificial Immune Network for Optimization

提出协作型人工免疫网络模型(CoAIN),实现基于全局粒子群的协作型人工免疫网络优化算法(gpso-CoAIN).算法中新增的全局粒子群协作算子使其人工免疫网络中的记忆细胞具有粒子的特性,能够通过个体间协作共享寻优经验.此外,改进的可变步长的克隆选择过程更适应高精度搜索.函数优化实验表明,gpso-CoAIN算法在寻优能力及执行速度方面都优于其它算法.对gpso-CoAIN人工免疫网络的动态特征分析表明,该算法的记忆细胞多样性良好.

A cooperative artificial immune network model is proposed. Inspired by global particle swarm intelligence, a cooperative artificial immune network, namely gpso-CoAIN, is developed for optimization. Due to the added global swarm cooperative operator, capable of sharing search experience. Furthermore, the of the artificial immune network is improved to adapt memory cells with particle swarm behavior are clone selection procedure with variable step size to fine optimal search. Experimental results of function optimization show that gpso-CoAIN outperforms several algorithms in optimal searching ability and running speed. The dynamic analysis illustrates the good diversity of the memory cells of the gpso-CoAIN network in the network population.