基于自适应混合蛙跳算法的水库调度研究

Study on Reservoir Scheduling based on Adaptive SFLA

针对传统混合蛙跳算法存在的问题,对SFLA的局部搜索策略进行改进,提出一种结合自适应局部搜索机制的改进混合蛙跳算法(MSFLA),并应用于水库优化调度研究中。通过将MSFLA与SFLA、DP对比,优化结果证明MSFLA在求解非线性、高维的水库优化调度问题中具有较好的有效性与优越性。

To improve the optimization capability of traditional shuffled frog leaping algorithm （SFLA）,a new modified shuffled frog leaping algorithm （MSFLA） by combining with new adaptive local search is proposed and used for optimal scheduling of reservoirs.By contrast with SFLA and DP ,the result proves that MSFLA has better effectiveness and superiority in solving nonlinear ,high dimensional reservoir optimal scheduling prob-lems.