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针对人工鱼群算法由于固定视野导致寻优效率低、易陷入局部极值的弊端,引入视野递减反馈策略,提出一种改进人工鱼群算法.视野随着迭代次数和寻优反馈信息适时变化,旨在平衡算法的全局搜索和局部搜索能力.实验测试表明算法在保证收敛速度的基础上提高了计算精度,并且增加了算法陷入局部极值时快速跳出的可能性,最后将改进算法应用于求解国家AAAAA级风景区最短遍历路径问题.
Aiming at the shortcomings of artificial fish swarm algorithm, such as fixed field of view, which results in low efficiency and easy to fall into local extremum, a descending feedback strategy is introduced to improve the artificial fish swarm algorithm.As the number of iterations and optimal feedback information changes in time, Which aims to balance the global search and local search ability of the algorithm.Experimental tests show that the algorithm improves the accuracy of the calculation based on the guarantee of convergence speed and increases the possibility of the algorithm jumping out of the local extreme quickly. Finally, the improved algorithm is applied to solving Shortest Traversal Path of National AAAAA Scenic Spot.