细菌觅食算法求解二次分配问题

Bacterial foraging algorithm for quadratic assignment problems

为有效解决二次分配问题,提出了一种基于群体搜索的群智能优化算法—细菌觅食算法。算法模拟了细菌觅食全过程,并将细菌个体信息与探索细菌群体信息进行结合,采用了群体搜索策略进行局部寻优。该策略有效的避免了算法陷入局部最优,而算法中采用的自适应搜索步长,进一步提高了优化的收敛速度。实验结果表明,用细菌觅食算法解决二次分配问题,并将仿真结果与其他算法进行比较,表明了该算法的搜索质量优于其他算法。

To solve the quadratic assignment problems efficiently, a new intelligent optimization algorithm based on group searching strategy is proposed called bacterial foraging optimization algorithm （BFO）. The bacteria feeding process is simulated, and the information of the bacterial individual is combined the bacterial group. It＇s efficiently to avoid the local optimization by a dopting the new strategy, and the adaptive search step length improves the optimization of the convergence speed. Compared to other algorithms indicate that this algorithm is better than the other algorithm in quality of optimization.