Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Trust region algorithms for optimization with nonlinear equality and inequality constraints
Trust region algorithms for optimization with nonlinear equality and inequality constraints
SIAM Journal on Numerical Analysis
Projected Quasi-Newton algorithm with trust region for constrained optimization
Journal of Optimization Theory and Applications
Large-scale nonlinear constrained optimization using trust regions
Large-scale nonlinear constrained optimization using trust regions
SIAM Journal on Optimization
A global convergence theory for a class of trust region algorithms for constrained optimization
A global convergence theory for a class of trust region algorithms for constrained optimization
Trust-region interior-point algorithms for a class of nonlinear programming problems
Trust-region interior-point algorithms for a class of nonlinear programming problems
| Hi-index | 0.48 |
A new trust-region active-set algorithm for solving minimizing a nonlinear function subject to nonlinear equality and inequality constraints is described. In this algorithm, an active set strategy is used together with a projected Hessian technique to compute the trial step.A convergence theory for this algorithm is presented. Under important assumptions, it is shown that the algorithm is globally convergent. In particular, it is shown that a subsequence of the iteration sequence is not bounded away from either Fritz-John points or KKT points.