A Regularized Sqp Method with Convergence to Second-order Optimal Points

@inproceedings{Gill2013ARS,
  title={A Regularized Sqp Method with Convergence to Second-order Optimal Points},
  author={Philip E. Gill and Vyacheslav Kungurtsev and Daniel P. Robinson},
  year={2013}
}
Regularized and stabilized sequential quadratic programming methods are two classes of sequential quadratic programming (SQP) methods designed to resolve the numerical and theoretical difficulties associated with ill-posed or degenerate nonlinear optimization problems. Recently, a regularized SQP method has been proposed that provides a strong connection between augmented Lagrangian methods and stabilized SQP methods. The method is formulated as a regularized SQP method with an implicit… CONTINUE READING
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