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Cited by 744Advanced Optimization Algorithms ResearchOptimization and Variational AnalysisComplexity and Algorithms in Graphs

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Variations and extension of the convex–concave procedure

Lipp, Thomas, Boyd, Stephen·2016·Optimization and Engineering
DOI 10.1007/s11081-015-9294-x
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  • Although the objective converges in all cases, it does not necessarily converge to a local minimum (Lipp & Boyd, 2016).

    “Although the objective converges in all cases, it does not necessarily converge to a local minimum (Lipp & Boyd, 2016).”

    From Hopfield Networks is All You Need (2020) · cites this paper as Lipp & Boyd, 2016

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Metadata

Authors
Lipp, T., & Boyd, S.
Affiliations
Stanford University (US)
Corresponding author
  • Lipp, Thomas
  • Boyd, Stephen
ORCID
Boyd, Stephen
Venue
Optimization and Engineering
Publisher
Springer Science and Business Media LLC
Published
2015-11-05
Volume
17
Issue
2
Pages
263-287
ISSN
  • 1389-4420 (ISSN-L)
  • 1573-2924
DOI
10.1007/s11081-015-9294-x
OpenAlex
W2221524898
Cited by
744
References
2
Citations by year
2026: 34 · 2025: 84 · 2024: 79 · 2023: 85 · 2022: 91 · 2021: 115 · 2020: 90 · 2019: 53 · 2018: 58 · 2017: 38 · 2016: 16 · 2015: 1
FWCI
42.51
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
Optimization and Engineering (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Optimization and Variational Analysis
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
Keywords
concave-convex procedure, difference of convex programming, local optima, traveling salesman problem, vector inequalities, local heuristics

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