Sequential Convex Optimization
Sequential Convex Optimization is an iterative numerical optimization technique that approximates a non-convex optimization problem by a sequence of convex subproblems, each constructed to locally approximate the original problem’s objective and constraints, thereby enabling efficient convergence to a stationary solution through successive refinement.
319
Publications
21.5K
Citations
803
Authors
324
Institutions
Publications per year
2017–2026
162
Variants
Successive Convex Optimization
Parents
319
1–5 of 319
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324
Stanford University
Stanford, United States
15 h-index
37 publications
3K citations

Beijing Institute of Technology
Beijing, China
11 h-index
32 publications
880 citations
KU Leuven
Leuven, Belgium
11 h-index
34 publications
1.5K citations
University of Illinois Urbana-Champaign
Urbana, United States
10 h-index
23 publications
1.7K citations
Jet Propulsion Laboratory
Pasadena, United States
9 h-index
14 publications
1.1K citations
Nanjing University of Posts and Telecommunications
Nanjing, China
8 h-index
26 publications
2.1K citations

National University of Defense Technology
Changsha, China
8 h-index
22 publications
2.3K citations

Rice University
Houston, United States
8 h-index
22 publications
1.6K citations
1–8 of 324
13 publications · 582 citations
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Repository · 8 publications · 259 citations
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8 publications · 862 citations
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8 publications · 464 citations
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8 publications · 327 citations
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