Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients

Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients (2001)

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by Ernesto G. Birgin , José Mario Martínez

Venue:	Computational Optimization and Applications
Citations:	50 - 10 self

BibTeX

@ARTICLE{Birgin01large-scaleactive-set,
    author = {Ernesto G. Birgin and José Mario Martínez},
    title = {Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients},
    journal = {Computational Optimization and Applications},
    year = {2001},
    volume = {23},
    pages = {101--125}
}

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Abstract

A new active-set method for smooth box-constrained minimization is introduced. The algorithm combines an unconstrained method, including a new line-search which aims to add many constraints to the working set at a single iteration, with a recently introduced technique (spectral projected gradient) for dropping constraints from the working set. Global convergence is proved. A computer implementation is fully described and a numerical comparison assesses the reliability of the new algorithm. Keywords: Box-constrained minimization, numerical methods, activeset strategies, Spectral Projected Gradient. 1

Citations

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