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Pattern-based Search of Epigenomic Data Using GeNemo
Published on: October 8, 2017
Data and performance of an active-set truncated Newton method with non-monotone line search for bound-constrained
A Cristofari1, M De Santis2, S Lucidi2
1Dipartimento di Matematica, Università di Padova, Via Trieste, 63, 35121 Padua, Italy.
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.
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