Research on a novel biogeography-based optimization algorithm based on evolutionary programming

Biogeography-based optimization(BBO) algorithm is a new global optimization algorithm. However,BBO lacks the explorative ability.In this paper,we proposed a novel hybrid BBO approach, called BBO-EP,which is characterized by 1) representing the individual as a real-coded parameter vector, and 2) combining Evolutionary Programming(EP) and BBO to enhance the explorative ability of BBO. Experiments have been conducted on 13 high-dimensional benchmark functions.And the results indicate the good performance of BBO-EP.Compared with the original BBO and the two EP approaches(FEP and CEP),experimental results show that our approach is better than the other approaches(BBO,FEP, and CEP) in terms of the quality of the final solutions.Moreover,the proposed BBO-EP is faster than the original BBO with respect to the convergence speed.