An improved hybrid biogeography-based optimization algorithm for constrained optimization problems

Constrained optimization problems are very important as they are encountered in many science and engineering applications. A hybrid method based on modified augmented Lagran- gian multiplier and biogeography-based optimization (BBO) algorithm is proposed to solve con- strained 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 BBO algorithm. Numerical results show that the proposed method is reliable and efficient for solving constrained optimization problems.