基于旋转状态转移的麻雀搜索算法

Sparrow search algorithm based on rotational state transition

针对现有的麻雀搜索算法(SSA)在接近全局最优时,种群多样性减少,容易陷入局部最优等问题,提出一种精英旋转策略的麻雀搜索优化算法(RLSSA)。首先,对麻雀种群中发现者进行旋转状态转移变换,以提高算法的局部搜索能力,提高算法的搜索精度。其次,对加入者引入基于莱维飞行的搜索策略,提高算法的全局搜索能力,同时引入贪婪算法搜索寻优策略。最后,在12个基础函数上进行仿真实验。实验结果表明上述方法在收敛速度和精度上有显著优势。

Aiming at the problems that the existing sparrow search algorithm(SSA)is close to the global optimum,the population diversity decreases and it is easy to fall into the local optimum,a sparrow search optimization algorithm(RLSSA)with elite rotation strategy is proposed.Firstly,the rotational state transition transformation of the discoverer in the sparrow population is carried out to improve the local search ability of the algorithm and improve the search accuracy of the algorithm.Secondly,the search strategy based on Levy flight is introduced to the joiners,which improves the global search ability of the algorithm,meanwhile introduces the greedy algorithm search optimization strategy.Finally,simulation experiments are carried out on 12 basic functions.Experimental results show that the above method has significant advantages in convergence speed and accuracy.