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Dettaglio pubblicazione

2018, DATA IN BRIEF, Pages 2155-2169 (volume: 21)

Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained optimization (01a Articolo in rivista)

Cristofari A., De Santis M., Lucidi S., Rinaldi F.

In this data article, we report data and experiments related to the research article entitled “A Two-Stage Active-Set Algorithm for Bound-Constrained Optimization”, by Cristofari et al. (2017). The method proposed in Cristofari et al. (2017), tackles optimization problems with bound constraints by properly combining an active-set estimate with a truncated Newton strategy. Here, we report the detailed numerical experience performed over a commonly used test set, namely CUTEst (Gould et al., 2015). First, the algorithm ASA-BCP proposed in Cristofari et al. (2017) is compared with the related method NMBC (De Santis et al., 2012). Then, a comparison with the renowned methods ALGENCAN (Birgin and Martínez et al., 2002) and LANCELOT B (Gould et al., 2003) is reported.
Gruppo di ricerca: Continuous Optimization
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