The research base on memetic meta-heuristic Shuffled Frog-Leaping Algorithm
Mei Yue, Tao Hu, Baoping Guo, Xuan Guo · 2009
Shuffled frog-leaping algorithm (SFLA) is a new meta-heuristic population evolutionary algorithm. Shuffled frog-leaping algorithm has fast and excellent global exploration capability. Firstly, the paper introduces the principle of SFLA. Then, the paper analyses the parameters of SFLA. By the examination, the paper validates the effect of parameters to SFLA. The paper compares SFLA with genetic algorithm (GA) and particle swarm optimization (PSO) by the testing function. we can find SFLA is better than GA and PSO in astringency and the global search capability.