Abstract
This paper presents a simple but efficient way to find a good initial
trust region radius in trust region methods for nonlinear
optimization. The method consists of monitoring the agreement between
the model and the objective function along the steepest descent
direction, computed at the starting point. Further improvements for
the starting point are also derived from the information gleaned
during the initializing phase. Numerical results on a large set of
problems show the impact the initial trust region radius may have on
trust region methods behaviour and the usefulness of the proposed
strategy.
Original language | English |
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Pages (from-to) | 1788-1803 |
Number of pages | 16 |
Journal | SIAM Journal on Scientific Computing |
Volume | 18 |
Issue number | 6 |
Publication status | Published - 1997 |