基于动态平衡因子自适应步长的布谷鸟搜索算法

针对标准布谷鸟搜索算法依赖Lévy飞行的游走导致整个搜索过程步长具有随机性的问题,提出一种基于动态平衡因子自适应步长的布谷鸟搜索算法。通过对标准布谷鸟搜索算法中参数偏度动态自适应取值来实现算法对步长的动态自适应,同时引入动态平衡因子以调节全局适应度和当前迭代次数所占的比重,从而实现布谷鸟搜索算法收敛速度和搜索精度的平衡。测试仿真实验结果表明,与标准布谷鸟搜索算法相比,提出的算法收敛速度显著提升;与单纯依赖迭代次数自适应步长的布谷鸟算法相比,提出的算法避免了为追求收敛速度而造成的算法早熟现象。

Self-adaptive Step Cuckoo Search Algorithm Based on Dynamic Balance Factor

Aiming at the problem that the standard cuckoo search algorithm relies on Lévy flights, which leads to the step length randomness of the search process, a self-adaptive step cuckoo search algorithm based on dynamic balance factor was proposed in this paper. The proposed algorithm realized the dynamic adaptation to the step length of the algorithm through the dynamic adaptation of the parameter in the standard cuckoo algorithm, and introduced the dynamic balance factor in order to adjust the proportion of the global fitness and the current iteration times to balance the convergence speed and search accuracy of the cuckoo search algorithm. The simulation results show that compared with the standard cuckoo algorithm, the convergence speed of the proposed algorithm is significantly improved. Compared with self-adaptive step cuckoo search algorithm which relies only on the iterative times, the proposed algorithm avoids the premature convergence of algorithms in the pursuit of convergence speed.