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A Limited Memory Algorithm for Bound Constrained Optimization

Richard H. Byrd; Peihuang Lu; Jorge Nocedal; Ciyou Zhu · SIAM Journal on Scientific Computing · 1995

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An algorithm for solving large nonlinear optimization problems with simple bounds is described. It is based on the gradient projection method and uses a limited memory BFGS matrix to approximate the Hessian of the objective function. It is shown how to take advantage of the form of the limited memory approximation to implement the algorithm efficiently. The results of numerical tests on a set of large problems are reported.

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APA 7

Byrd, R. H, Lu, P, Nocedal, J, & Zhu, C. (1995). A Limited Memory Algorithm for Bound Constrained Optimization. https://doi.org/10.1137/0916069

MLA

Byrd, Richard H, et al. "A Limited Memory Algorithm for Bound Constrained Optimization." 1995. https://doi.org/10.1137/0916069.

Chicago

Byrd, Richard H, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu. 1995. "A Limited Memory Algorithm for Bound Constrained Optimization.". https://doi.org/10.1137/0916069.

Harvard

Byrd, R. H. et al. 1995, A Limited Memory Algorithm for Bound Constrained Optimization, SIAM Journal on Scientific Computing, available at: https://doi.org/10.1137/0916069 [Accessed 7 Aug. 2026].

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Title
A Limited Memory Algorithm for Bound Constrained Optimization
Author / contributors
Richard H. Byrd; Peihuang Lu; Jorge Nocedal; Ciyou Zhu
Publisher
SIAM Journal on Scientific Computing
Publication year
1995
Language
English

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