非劣解变异蛙跳算法

Non-inferior Solution Variants Frog Leaping Algorithm

针对基本蛙跳算法搜索速度和精度不高的缺点,将变异的思路融入基本蛙跳算法,提出了一种非劣解变异蛙跳算法.算法充分利用蛙群的群体信息,对青蛙子族群中的若干非劣解结合自身信息和群体信息进行变异,避免了算法陷入局部最优,并大幅度提高了算法的搜索速度.实验表明,改进后的算法收敛速度以及收敛精度方面都比基本蛙跳算法有了很大程度的提高,同时,该算法与相关文献中的算法进行比较发现,其性能有较大的提高.

As the search speed and accuracy of the basic frog leaping algorithm is not high,this article integrates the idea of variation into the basic frog leaping algorithm（SFLA）and proposes a new improved shuffled frog leaping algorithm which is called Non-inferior solution variants frog leaping algorithm（NSFLA）.The algorithm makes full use of the information of frog population groups to complete the variant of some non-inferior solutions by combining their own information and the group information.This method can avoid falling into local optimum.At the same time,it can also greatly increase the searching speed of the algorithm.The experimental results reveal that NSFLA is better than SFLA in convergence velocity and convergence precision.Comparing NSFLA with the algorithms in some documents,we find the performance of NSFLA better.