A Global Convergence Theory for a General Class of Trust-region-based Algorithms for Constrained Optimization without Assuming Regularity a Global Convergence Theory for a General Class of Trust-region-based Algorithms for Constrained Optimization without Assuming Regularity

@inproceedings{ElAlem1997AGC,
  title={A Global Convergence Theory for a General Class of Trust-region-based Algorithms for Constrained Optimization without Assuming Regularity a Global Convergence Theory for a General Class of Trust-region-based Algorithms for Constrained Optimization without Assuming Regularity},
  author={Mahmoud El-Alem},
  year={1997}
}
This work presents a convergence theory for a general class of trust-region-based algorithms for solving the smooth nonlinear programming problem with equality constraints. The results are proved under very mild conditions on the quasi-normal and tangential components of the trial steps. The Lagrange multiplier estimates and the Hessian estimates are… CONTINUE READING