融合柯西扰动与种群优化的布谷鸟算法

Cuckoo Algorithm Under the Combination of Cauchy Perturbation with Population Optimization

针对传统布谷鸟算法存在的初始种群多样性差、面对高维复杂问题极易陷入局部最优解的问题,采用Tent混沌映射优化初始种群,使初始种群具有更好的便利性,对多次迭代中当代最优值不变的种群进行柯西扰动,提高算法跳出局部最优解的能力。采用7种不同类型的测试函数与CS、PSO、DE3种对比算法,验证改进算法的寻优能力。结果表明,对于不同类型的测试函数,改进的算法较传统算法在寻优速度与精度方面均有所提高。

Aiming at the problem that traditional cuckoo algorithm has poor initial population diversity and easily falls into local optimal solution in the face of high-dimensional complex problems,Tent chaotic mapping is used to optimize the initial population,so that the initial population has better convenience,and then Cauchy disturbance is performed on the population with constant contemporary optimal value in multiple iterations to improve the ability of the algorithm to jump out of the local optimal solution.7 different types of test functions are compared with CS,PSO and DE to verify the optimization ability of improved algorithm.The results show that for different types of test functions,the improved algorithm has improved the optimization speed and accuracy compared with the traditional algorithm.