CasADi

CasADi: A symbolic package for automatic differentiation and optimal control. We present CasADi, a free, open-source software tool for fast, yet efficient solution of nonlinear optimization problems in general and dynamic optimization problems in particular. To the developer of algorithms for numerical optimization and to the advanced user of such algorithms, it offers a level of abstraction which is notably lower, and hence more flexible, than that of algebraic modeling languages such as AMPL or GAMS, but higher than working with a conventional automatic differentiation (AD) tool. par CasADi is best described as a minimalistic computer algebra system (CAS) implementing automatic differentiation in eight different flavors. Similar to algebraic modeling languages, it includes high-level interfaces to state-of-the-art numerical codes for nonlinear programming, quadratic programming and integration of differential-algebraic equations. CasADi is implemented in self-contained C++ code and contains full-featured front-ends to Python and Octave for rapid prototyping. In this paper, we present the AD framework of CasADi and benchmark the tool against AMPL for a set of nonlinear programming problems from the CUTEr test suite.


References in zbMATH (referenced in 22 articles , 2 standard articles )

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  1. Chen-Charpentier, Benito M.; Jackson, Mark: Direct and indirect optimal control applied to plant virus propagation with seasonality and delays (2020)
  2. Himmel, Andreas; Sager, Sebastian; Sundmacher, Kai: Time-minimal set point transition for nonlinear SISO systems under different constraints (2020)
  3. Köhler, Johannes; Müller, Matthias A.; Allgöwer, Frank: A nonlinear tracking model predictive control scheme for dynamic target signals (2020)
  4. Liao-McPherson, Dominic; Nicotra, Marco M.; Kolmanovsky, Ilya: Time-distributed optimization for real-time model predictive control: stability, robustness, and constraint satisfaction (2020)
  5. Qian, George; Mahdi, Adam: Sensitivity analysis methods in the biomedical sciences (2020)
  6. Zanelli, A.; Domahidi, A.; Jerez, J.; Morari, M.: FORCES NLP: an efficient implementation of interior-point methods for multistage nonlinear nonconvex programs (2020)
  7. Andersson, Joel A. E.; Gillis, Joris; Horn, Greg; Rawlings, James B.; Diehl, Moritz: CasADi: a software framework for nonlinear optimization and optimal control (2019)
  8. Chris Rackauckas, Mike Innes, Yingbo Ma, Jesse Bettencourt, Lyndon White, Vaibhav Dixit: DiffEqFlux.jl - A Julia Library for Neural Differential Equations (2019) arXiv
  9. Kouzoupis, D.; Klintberg, E.; Frison, G.; Gros, S.; Diehl, M.: A dual Newton strategy for tree-sparse quadratic programs and its implementation in the open-source software treeQP (2019)
  10. Olsen, Christian Haargaard; Ottesen, Johnny T.; Smith, Ralph C.; Olufsen, Mette S.: Parameter subset selection techniques for problems in mathematical biology (2019)
  11. Robin Verschueren, Gianluca Frison, Dimitris Kouzoupis, Niels van Duijkeren, Andrea Zanelli, Branimir Novoselnik, Jonathan Frey, Thivaharan Albin, Rien Quirynen, Moritz Diehl: acados: a modular open-source framework for fast embedded optimal control (2019) arXiv
  12. Birk, Lothar; McCulloch, T. Luke: Robust generation of constrained B-spline curves based on automatic differentiation and fairness optimization (2018)
  13. Jason K. Moore; Antonie van den Bogert: opty: Software for trajectory optimization and parameter identification using direct collocation (2018) not zbMATH
  14. Jordan Jalving, Yankai Cao, Victor M. Zavala: Graph-Based Modeling and Simulation of Complex Systems (2018) arXiv
  15. Le, Thuy T. T.; Jost, Felix; Sager, Sebastian: Optimal control of vibration-based micro-energy harvesters (2018)
  16. Magnusson, Fredrik; Åkesson, Johan: Symbolic elimination in dynamic optimization based on block-triangular ordering (2018)
  17. Dunning, Iain; Huchette, Joey; Lubin, Miles: JuMP: a modeling language for mathematical optimization (2017)
  18. Quirynen, Rien; Gros, Sébastien; Houska, Boris; Diehl, Moritz: Lifted collocation integrators for direct optimal control in ACADO toolkit (2017)
  19. Elsheikh, Atiyah: An equation-based algorithmic differentiation technique for differential algebraic equations (2015)
  20. Word, Daniel P.; Kang, Jia; Akesson, Johan; Laird, Carl D.: Efficient parallel solution of large-scale nonlinear dynamic optimization problems (2014)

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