Studying Parameter of MEC Used to Multi-modal Optimization by Two-Level MEC

Mind evolutionary computation (MEC) is a new approach of evolution computation that was proposed in 1998 by Chengyi Sun. It has excellent performances on various aspects. For using MEC to optimize multi-modal functions better, studied the parameter Nm in peak radius MEC. In this paper, a two-level MEC algorithm was built, in which the high-level MEC was adopted to optimize the parameters of the low-level MEC for multi-modal optimization. Used this two-level MEC to carry out experiments to study the influence of different value of Nm on the precisions of solutions found. The results show solution found is more precise with the Nm increasing.