A Global Convergence Theory for a Trust-Region Algorithm for Constrained Optimization Which Does Not Assume Linear Independence
A trust-region algorithm for solving the equality constrained optimization problem is presented. This algorithm uses Byrd and Omojokun's way of computing the trial steps, but it differs from the Byrd and Omojokun algorithm in the way steps are evaluated. A global convergence theory for this new algorithm is presented. The main feature of this theory is that the linear independence assumption on the gradients of the constraints is not assumed.
Citable link to this pagehttps://hdl.handle.net/1911/101821
MetadataShow full item record
- CAAM Technical Reports