A novel hybrid algorithm for global optimization based on EO and SFLA
Jian-ping Luo, Min-Rong Chen, Xia Li · 2009
In this study, we have presented a new hybrid optimization method, called hybrid shuffled frog leaping algorithm and extremal optimization algorithm (SFLA-EO) which introduces EO to SFLA. SFLA-EO combines the merits of both SFLA and EO by drawing on the local-search strategy from EO and global-search strategy from SFLA. The results of experiments carried out with six well-known benchmark functions have shown the proposed algorithm possesses outstanding performance in convergence speed, robustness and stability, as compared to standard PSO, SFLA and EO. It is proved that the SFLA-EO algorithm is very effective and superior to solve continuous global optimization problems.