A TRUST REGION ALGORITHM WITH NULL SPACE TECHNIQUE FOR EQUALITY CONSTRAINED OPTIMIZATION

摘要

This paper presents a trust region algorithm with null space technique for nonlinear equality constrained optimization. Considering in the null space methods that, the convergent rate of range space step is faster than the null space step for the most cases, the proposed algorithm computes null steps more often than range space step. Moreover, the new algorithm is based on the reduced Hessian SQP method. Global convergence of the proposed algorithm is proved. The effectiveness of the method is demonstrated by some numerical examples.