A Trust Region Strategy for Nonlinear Equality Constrained Optimization
Celis, Maria Rosa
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/15885
Many current algorithms for nonlinear constrained optimization problems determine a search direction by solving a quadratic programming subproblem. The global convergence properties are addressed by using a line search technique and a merit function to modify the length of the step obtained from the quadratic program. In unconstrained optimization, trust region strategies have been very successful. In this thesis we present a new approach for equality constrained optimization problems based on a trust region strategy. The direction selected is not necessarily the solution of the standard quadratic programming subproblem.
Citable link to this pagehttps://hdl.handle.net/1911/101581
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