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CasADi: a software framework for nonlinear optimization and optimal control

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Andersson, Joel A. E., Gillis, Joris, Horn, Greg, Rawlings, James B., Diehl, Moritz·2019·Mathematical Programming Computation

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Cited by

See all 3,868

Metadata

Authors
Andersson, J. A. E., Gillis, J., Horn, G., Rawlings, J. B., & Diehl, M.
Venue
Mathematical Programming Computation
Published
2018-07-11
Volume
11
Issue
1
Pages
1-36
ISSN
  • 1867-2949 (ISSN-L)
  • 1867-2957
OpenAlex
W2842089854
Cited by
3,868
References
2
FWCI
190.20
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: CasADi: a software framework for nonlinear optimization and optimal control. https://app.cochat.ai/papers/10.1007/s12532-018-0139-4
The paper
Andersson, J. A. E., Gillis, J., Horn, G., Rawlings, J. B., & Diehl, M. (2019). CasADi: a software framework for nonlinear optimization and optimal control. Mathematical Programming Computation. https://doi.org/10.1007/s12532-018-0139-4

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.