Mind evolutionary computation for the constrained optimization

In this paper, the mind evolutionary computation (MEC) was applied to solve the constrained optimization problems. First, several concepts are presented and a valid method to handle the constraints is developed based on those concepts. After that, according to the features of the constrained problems, the 'similartaxis' and dissimilation operators in MEC are redesigned in details. Finally, the simulation results for the nonlinear constrained problem show the effectiveness of the algorithm in solving the constrained problems.