Large-Scale Nonlinear Programming is a mathematical optimization framework that belongs to the class of nonlinear programming problems and is distinguished by its treatment of systems involving a large number of decision variables and constraints, typically requiring specialized algorithms and computational strategies to address their inherent complexity and scale.
219
Publications
37.5K
Citations
449
Authors
224
Institutions
Publications per year
2017–2026
29
Parents
Publications
219
A Limited Memory Algorithm for Bound Constrained Optimization
Richard H. Byrd, Peihuang Lu, Jorge Nocedal et al. · SIAM Journal on Scientific Computing · 1995 · 6.2K citations
Ciyou Zhu, Richard H. Byrd, Peihuang Lu et al. · ACM Transactions on Mathematical Software · 1997 · 3.4K citations · Full text
1–5 of 219
Authors
449
- LT
16
h-index
- PL
7
h-index
- SA
6
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- VM
6
h-index
- LS
6
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1–5 of 449
Institutions
224
Carnegie Mellon University
Pittsburgh, United States
15 h-index
28 publications
12.2K citations
Northwestern University
Evanston, United States
7 h-index
14 publications
11K citations
Guangxi University
Nanning, China
6 h-index
14 publications
509 citations
The University of Texas at Austin
Austin, United States
6 h-index
11 publications
652 citations
Princeton University
Princeton, United States
5 h-index
10 publications
1.1K citations
University of Wisconsin–Madison
Madison, United States
5 h-index
7 publications
262 citations
University of Namur
Namur, Belgium
5 h-index
6 publications
553 citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
11 publications
785 citations
1–8 of 224
Venues
- SIAM Journal on Optimization
13 publications · 2.3K citations
12
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- Computers & Chemical Engineering
13 publications · 1.4K citations
12
h-index
- Optimization methods & software
8 publications · 368 citations
8
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- Mathematical Programming
8 publications · 10.2K citations
8
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- Annals of Operations Research
8 publications · 315 citations
8
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