Starting from the paper by Nash and Sofer (1990), we propose a heuristic adaptive truncation criterion for the inner iterations within linesearch-based truncated Newton methods. Our aim is to possibly avoid âover-solvingâ 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.
Fasano, Giovanni (Corresponding)
|Data di pubblicazione:||2018|
|Titolo:||An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization|
|Rivista:||OPERATIONS RESEARCH LETTERS|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.orl.2017.10.014|
|Appare nelle tipologie:||2.1 Articolo su rivista |