Research on Improved Strategy of Shuffled Frog Leaping Algorithm

The shuffled frog leaping algorithm (SFLA) is suitable for solving various combinatorial optimization problems. However, the algorithm has the disadvantages of slow convergence, easy to fall into the local optimal solution and premature convergence. Therefore, this paper will improve the classic SFLA from the introduction of adaptive mobility factor and the update strategy of sub-population frog individuals, and carry out simulation comparison experiments. The results show that the improved SFLA effectively improves the search accuracy and convergence speed.