改进的细菌觅食算法

Improved Bacterial Foraging Algorithm

为提高细菌觅食算法的性能,将免疫算法与细菌觅食算法融合,利用免疫算法的克隆选择思想代替细菌觅食算法的复制操作;在趋向性操作中,随着迭代的进行,逐步缩小细菌运动步长,在保证细菌收敛性的同时增强细菌的全局搜索性能;改进迁移操作,保证适应度值最高的细菌不被驱散,以提高收敛精度。仿真表明,优化后的算法得到最优值比BFA(Bacterial Foraging Algorithm)的最优值更靠近函数的最优值,证明其寻优能力更强,且3个函数的方差均小于BFA的方差,证明其稳定性也更好。

In order to improve the performance of the BFA（ Bacterial Foraging Algorithm）,Bacterial foraging algorithm and immune algorithm were combined,the clonal selection ideas in immune algorithm were used to replace the reproduction operation of BFA. For the chemotaxis operation,the moving step of bacteria is shorten by the iteration proceeding,so that the astringency is guaranteed,and the overall searching capability of bacteria is ensured. The elimination and dispersal operation is improved by guaranteeing the bacterial with the highest fitting value not be dispelled to increase the astirngency accuracy. The results show that the optimal value which was obtained by the authors were closer to the optimal value than BFA＇s,which proved the algorithm was more capable in optimization. Moreover,the algorithm was more stable because the variance of three functions were all less than BFA＇s.