An effective hybrid evolutionary algorithm for constrained engineering optimization

A hybrid method based on modified augmented Lagrangian multiplier and composite evolutionary algorithm is proposed to solve constrained optimization problems. The basic steps of the proposed method are comprised of an outer iteration, in which the Lagrangian multipliers and various penalty parameters are updated using a first-order update scheme, and an inner iteration, in which a nonlinear optimization of the modified augmented Lagrangian function with simple bound constraints is implemented by composite evolutionary algorithm, which combining several effective crossover operators with some suitable mutation operators. Numerical simulation results show that the proposed method can yield better solutions than those reported in the literature for most problems.