求解约束优化问题的一类新型混合方法

onstrained optimization problem is a widespread and complex application problem in practical engineering. Firstly, a modified augmented Lagrange function is formulated via the object function, equality constraints and inequality constraints. The general nonlinear constrained optimization is then converted as a bound constrained optimization. Secondly, a global search for the modified augmented Lagrange function is done under the bound constraints. The Lagrangian multipliers and various penalty parameters are then updated according to the obtained information. Thirdly, a new hybrid method for constrained optimization problem is proposed by coupling modified augmented Lagrange multiplier method and particle swarm optimization. Finally, the numerical experiences on thirteen benchmark problems are provided to demonstrate the computational efficiency of the proposed hybrid method.