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Cited by 1,739

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

An Interior Point Algorithm for Large-Scale Nonlinear Programming

Byrd, Richard H., Hribar, Mary E., Nocedal, Jorge·1999·SIAM Journal on Optimization

Abstract

The design and implementation of a new algorithm for solving large nonlinear programming problems is described. It follows a barrier approach that employs sequential quadratic programming and trust regions to solve the subproblems occurring in the iteration. Both primal and primal-dual versions of the algorithm are developed, and their performance is illustrated in a set of numerical tests.

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Metadata

Authors
Byrd, R. H., Hribar, M. E., & Nocedal, J.
Venue
SIAM Journal on Optimization
Published
1999-01
Volume
9
Issue
4
Pages
877-900
ISSN
  • 1052-6234 (ISSN-L)
  • 1095-7189
OpenAlex
W1971536112
Cited by
1,739
References
1
FWCI
18.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An Interior Point Algorithm for Large-Scale Nonlinear Programming. https://app.cochat.ai/papers/10.1137/s1052623497325107
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Byrd, R. H., Hribar, M. E., & Nocedal, J. (1999). An Interior Point Algorithm for Large-Scale Nonlinear Programming. SIAM Journal on Optimization. https://doi.org/10.1137/s1052623497325107

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.