A New Shuffled Frog Leaping Algorithm with Space Zoomed Factor and Gravity Attractor

Shuffled frog leaping algorithm is a new kind of swarm intelligence optimization algorithm. Due to the local search of the basic shuffled frog leaping algorithm which is the only by the worst frog to search and jump, searching ability of which was limited; therefore it had the low precision, slow convergence speed and easy premature convergence etc. Therefore, in order to enhance the ability of the local searching, this paper presented a gravity attractor, all the frogs in the same memeplexe could find the best position under its guidance. Considering the transboundary problems in the frog searching for food process, we introduced a space zoomed factor which made the frog out of the searching space could also be put into the searching space, and the social position relation was not changed, thus it improve the search ability of the SFLA. Through the standard function for testing, and compared with the standard SFLA algorithm and szAPSO algorithm, the experimental results show that the improved algorithm not only improves the convergence speed of the algorithm, enhance the searching capability of the algorithm, but also has better stability.