Projects per year
Abstract
A class of trust region based
algorithms is presented for the solution of nonlinear optimization
problems with a convex feasible set. At variance with previously
published analysis of this type, the theory presented allows for the
use of general norms. Furthermore, the proposed algorithms do not
require the explicit computation of the projected gradient, and can
therefore be adapted to cases where the projection onto the feasible
domain may be expensive to calculate. Strong global convergence
results are derived for the class. It is also shown that the set of
linear and nonlinear constraints that are binding at the solution are
identified by the algorithms of the class in a finite number of
iterations.
Original language | English |
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Pages (from-to) | 164-221 |
Number of pages | 58 |
Journal | SIAM Journal on Optimization |
Volume | 3 |
Issue number | 1 |
Publication status | Published - 1993 |
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LANCELOT: LANCELOT, a package for the solution of large-scale nonlinear optimization problems
TOINT, P., Sartenaer, A., Gould, N. I. M. & Conn, A.
1/09/87 → 1/09/00
Project: Research
Student theses
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On some strategies for handling constraints in nonlinear optimization
Author: Sartenaer, A., 1991Supervisor: Toint, P. (Supervisor), Conn, A. (External person) (Jury), Sachs, E. (External person) (Jury), Nguyen, V. H. (Jury) & Strodiot, J. (Jury)
Student thesis: Doc types › Doctor of Sciences