An Algorithm for Global Optimization Based on CFO-BFGS

Evolutionary algorithm has some drawbacks, such as premature convergence. To overcome these problems, this article proposed a hybrid algorithm of Central Force Optimization (CFO) and BFGS method. A new mutation operator are constructed to balance the exploration and exploitation. Several benchmark functions are selected to test the validity of hybrid algorithm. The numerical experiment results show that new algorithm is effective for solving global optimization problems.