Abstract: Shuffled Frog Leaping Algorithm (SFLA) is a population-based novel and effective mcta-heuristics computing method, which received increasing focuses from academic and engineering optimization fields in recent years. Since SFLA is a combination of Mcmctic Algorithm (MA) with strong Local Search (LS) ability and Particle Swarm Optimination (PSO) with good Global Search (GS) capability, it is of strong optimum-searching power and easy to be implemented. In this paper, the fundamental principles and framework of SFLA were described. Then, the related researches of SFLA in the current optimization and engineering fields were summed up. Lastly, the future perspectives of SFLA were presented.

Key words: Shuffled frog leaping algorithm, Meta-heuristics algorithm, Engineering optimization, Mcmetic algorithm,Particle swarm optimization