Starting from the paper by Nash and Sofer (1990), we propose a heuristic adaptive truncation criterionfor 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.
2018, OPERATIONS RESEARCH LETTERS, Pages 7-12 (volume: 46)
An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization (01a Articolo in rivista)
Caliciotti Andrea, Fasano Giovanni, Nash Stephen G., Roma Massimo
Gruppo di ricerca: Continuous Optimization