During adjustment process, a creative method named reverse adjustment was adopted, to prevent the algorithm from being got in local optimization trap.

该算法的基本思路是边构造边调整路径，在调整中采用了独创的逆向调整方法，避免算法陷入局部优化陷阱。

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But the algorithm easily trapped into local optimal solution and solved the problem more slowly, this paper constructed Max-Min ACO algorithm through the improvement and adjustment of ACO algorithm.

针对该算法易陷入局部最优解、求解速度较慢的缺陷，本文通过对蚁群算法的改进和调整，构造出最大—最小蚁群算法。

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A modified BP algorithm of neural network, random adjustment of parameters (RMBP) algorithm, is proposed to overcome the defect of easy going into local minimum of BP neural network.

针对BP(反向传播)神经网络学习易陷入局部极小的缺陷，提出了一种改进BP神经网络学习算法——RMBP算法。

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