An Opposition-Based Chaos Shuffled Frog Leaping Algorithm

In order to overcome the defects of shuffled frog leaping algorithm (SFLA) such as slow searching speed in the late evolution and easily trapping into local extremum, an Opposition-based Chaos Shuffled Frog Leaping Algorithm (OCSFLA) was originally proposed in this paper. It utilized the opposition strategy to generate initial population, adopted a modified frog leaping updating formula, and combined the frog population movement with the chaotic motion, thus putting forward a chaos shuffled frog leaping optimization model. Tests on five standard test functions show that OCSFLA has an obvious improvement in whatever the convergence precision, the convergence speed, the optimization time as well as the stability.