Numerical Experience with Iterative Methods for Equality Constrained Nonlinear Programming Problems

0404487 - UIVT-O 20010142 RIV US eng J - Journal Article
Lukšan, Ladislav - Vlček, Jan
Numerical Experience with Iterative Methods for Equality Constrained Nonlinear Programming Problems.
Optimization Methods & Software. Roč. 16, č. 1-4 (2001), s. 257-287. ISSN 1055-6788. E-ISSN 1029-4937
R&D Projects: GA ČR GA201/00/0080
Institutional research plan: AV0Z1030915
Keywords : nonlinear equations * sparse problems * equality constraints * inexact Newton method * line search methods * indefinite systems * indefinite preconditioners * symmetric Krylov subspace methods * residual smoothing * computational experiments
Subject RIV: BB - Applied Statistics, Operational Research
Impact factor: 0.623, year: 2001

We show that indefinitely preconditioned symmetric Krylov-subspace methods are very efficient for solving linearized KKT systems arising in equality constrained optimization. We give a numerical comparison of various Krylov subspace methods in three different forms (original system, null-space transformation, range-space transformation). Furthermore, we give a survey of our previous results concerning indefinite preconditioners and merit functions and prove new propositions.
Permanent Link: http://hdl.handle.net/11104/0124740