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CasADi: a software framework for nonlinear optimization and optimal control

  • Joel A. E. Andersson
  • Joris Gillis
  • Greg Horn
  • James B. Rawlings
  • Moritz Diehl
Full Length Paper

Abstract

We present CasADi, an open-source software framework for numerical optimization. CasADi is a general-purpose tool that can be used to model and solve optimization problems with a large degree of flexibility, larger than what is associated with popular algebraic modeling languages such as AMPL, GAMS, JuMP or Pyomo. Of special interest are problems constrained by differential equations, i.e. optimal control problems. CasADi is written in self-contained C++, but is most conveniently used via full-featured interfaces to Python, MATLAB or Octave. Since its inception in late 2009, it has been used successfully for academic teaching as well as in applications from multiple fields, including process control, robotics and aerospace. This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last 7 years.

Keywords

Optimization Optimal control Open source optimization software 

Mathematics Subject Classification

90C99 93A30 97A01 

Notes

Acknowledgements

The authors thank for the generous support that has made this work possible. In particular: the K.U. Leuven Research Council via CoE EF/05/006 Optimization in Engineering (OPTEC); the Flemish Government via FWO; the Belgian State via Science Policy programming (IAP VII, DYSCO); the European Union via HDMPC (223854), EMBOCON (248940), HIGHWIND (259166), TEMPO (607957), AWESCO (642682); the Helmholtz Association via vICERP; the German Federal Ministry for Economic Affairs and Energy (BMWi) via projects eco4wind and DyConPV; the German Research Foundation (DFG) via Research Unit FOR 2401; Flanders Make via MBSE4M, Drivetrain Co-design, Conceptdesign. We also thank our industrial partners, including GE Global Research and Johnson Controls International Inc. Finally, we thank the reviewers for valuable comments that helped to improve the final manuscript.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature and The Mathematical Programming Society 2018

Authors and Affiliations

  • Joel A. E. Andersson
    • 1
  • Joris Gillis
    • 2
    • 3
  • Greg Horn
    • 4
  • James B. Rawlings
    • 1
  • Moritz Diehl
    • 5
  1. 1.Department of Chemical and Biological EngineeringUniversity of Wisconsin-MadisonMadisonUSA
  2. 2.MECO Research Team, Department Mechanical EngineeringKU LeuvenLeuvenBelgium
  3. 3.DMMS LabFlanders MakeLeuvenBelgium
  4. 4.Kitty HawkMountain ViewUSA
  5. 5.Department of Microsystems Engineering IMTEKUniversity of FreiburgFreiburgGermany

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