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.

Cristofari, A., De Santis, M., Lucidi, S., Rinaldi, F. (2018). Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained optimization. DATA IN BRIEF, 21, 2155-2169 [10.1016/j.dib.2018.11.061].

Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained optimization

Cristofari A.;
2018-01-01

Abstract

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.
2018
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore MAT/09 - RICERCA OPERATIVA
English
https://www.sciencedirect.com/science/article/pii/S2352340918314549?via=ihub
Cristofari, A., De Santis, M., Lucidi, S., Rinaldi, F. (2018). Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained optimization. DATA IN BRIEF, 21, 2155-2169 [10.1016/j.dib.2018.11.061].
Cristofari, A; De Santis, M; Lucidi, S; Rinaldi, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/312071
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