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An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization. (English) Zbl 07064413
Summary: Starting from the paper by the third author and A. Sofer [ibid. 9, No. 4, 219–221 (1990; Zbl 0706.90073)], we propose a heuristic adaptive truncation criterion for the inner iterations within linesearch-based truncated Newton methods. Our aim is to possibly avoid “over-solving” of the Newton equation, based on a comparison between the predicted reduction of the objective function and the actual reduction obtained. A numerical experience on unconstrained optimization problems highlights a satisfactory effectiveness and robustness of the adaptive criterion proposed, when a residual-based truncation criterion is selected.

90-XX Operations research, mathematical programming
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