分析了人工鱼群算法存在的问题, 提出一种改进人工鱼群算法, 并将其用于梯级水库群的优化调度. 其改进思想是采用动态调整人工鱼视野和步长的方法, 较好地平衡了人工鱼群算法的全局搜索能力和局部搜索能力的矛盾; 在此基础上, 针对算法局部更新策略引起的更新操作前后个体空间位置变化较大, 降低收敛速度这一问题, 在局部更新时采用了阈值选择的策略. 通过实例验证了该改进算法的有效性, 并对改进算法的阈值参数进行了率定.

To improve the optimization capability of traditional artificial fish swarm algorithm (AFSA), an improved AFSA is proposed and used for optimal operation for cascade reservoirs. The dynamic adjustment method for the vision and step of artificial fish is adopted in improved ASFA, which can improve the abilities of searching the global and local extremum. Then, aiming at the problem of low convergence speed induced by the large individual space gap between before and after update operation, the threshold selection strategy is used in the local update operation. Finally, the validity of the improved AFSA is verified through case study, and the threshold parameters are also calibrated by numerical experiment.