改进的混合蛙跳算法

为提高混合蛙跳算法在优化问题求解中的性能,提出了一种改进混合蛙跳算法。改进算法在原算法基础上加入了变异算子,并根据算法进化过程的不同阶段和进化过程中候选解分布情况，利用模糊控制器对变异算子的变异尺度进行调整，实现了变异算子在解空间中搜索范围的动态调整。通过对优化问题中4个典型测试函数的仿真实验表明,与基本蛙跳算法和已有改进算法相比，改进算法在寻优精度、收敛速度和求解成功率上均有一倍以上的提高,尤其在高维复杂优化问题求解中体现出较强的寻优能力。

Improved shuffled frog leaping algorithm

To enhance the performance of Shuffled Frog Leaping Algorithm (SFLA) in solving optimization problems，this paper proposed an improved shuffled frog leaping algorithm. By adding mutation operator to the original algorithm, the improved algorithm regulated the scale of mutation operator via fuzzy controller, made a dynamic adjustment of mutation operator in the searching range of solution space with different phase and candidate solution distribution of evolution process. The simulation results of four typical functions of optimization problems show that the proposed algorithm can attain above twice improvement on accuracy, convergent speed and success rate, and it demonstrates a better optimization capability especially in solving the high dimensional complex optimization problem, in comparison with the basic shuffled frog leaping algorithm and the known improved algorithm.