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Abstract
We introduce a new algorithm for the solution of systems of nonlinear equations and nonlinear least-squares problems that attempts to combine the efficiency of filter techniques and the robustness of trust-region methods. The algorithm is shown, under reasonable assumptions, to globally converge to zeros of the system, or to first-order stationary points of the Euclidean norm of its residual. Preliminary numerical experience is presented that shows substantial gains in efficiency over the traditional monotone trust-region approach. © 2004 Society for Industrial and Applied Mathematics.
Original language | English |
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Pages (from-to) | 17-38 |
Number of pages | 22 |
Journal | SIAM Journal on Optimization |
Volume | 15 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2005 |
Keywords
- least-squares methods
- filter methods
- nonlinear equations
- Nonlinear optimization
- convergence theory
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ADALGOPT: ADALGOPT - Advanced algorithms in nonlinear optimization
Sartenaer, A. (CoI) & Toint, P. (CoI)
1/01/87 → …
Project: Research Axis
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Filter methods for nonlinear problems
Toint, P. (PI) & SAINVITU, C. (Researcher)
2/02/02 → 31/08/11
Project: Research