A New Convergence Theory for Trust-Region Algorithm for Solving Constrained Optimization Problems
نویسنده
چکیده
In this paper, we propose a new trust-region algorithm for solving a constrained optimization problem with equality and inequality constraints. In this algorithm, an active-set technique is used to convert the constrained optimization problem with equality and inequality constraints to equality constrained optimization problem. A projected Hessian technique is used together with a conjugate gradient method to compute the trial step. Global convergence results are established under important assumptions and it is shown that a subsequence of the iteration sequence is not bounded away from KKT points. Preliminary numerical experiment on the algorithm is presented. The performance of the algorithm is reported. The numerical results show that our approach is of value and merit further investigation.
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