Ipopt

Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt) is a software package for large-scale ​nonlinear optimization. It is designed to find (local) solutions of mathematical optimization problems of the from min f(x), x in R^n s.t. g_L <= g(x) <= g_U, x_L <= x <= x_U, where f(x): R^n --> R is the objective function, and g(x): R^n --> R^m are the constraint functions. The vectors g_L and g_U denote the lower and upper bounds on the constraints, and the vectors x_L and x_U are the bounds on the variables x. The functions f(x) and g(x) can be nonlinear and nonconvex, but should be twice continuously differentiable. Note that equality constraints can be formulated in the above formulation by setting the corresponding components of g_L and g_U to the same value. Ipopt is part of the ​COIN-OR Initiative.


References in zbMATH (referenced in 740 articles )

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  1. Arrigo, Adriano; Ordoudis, Christos; Kazempour, Jalal; De Grève, Zacharie; Toubeau, Jean-François; Vallée, François: Wasserstein distributionally robust chance-constrained optimization for energy and reserve dispatch: an exact and physically-bounded formulation (2022)
  2. Brust, Johannes J.; Marcia, Roummel F.; Petra, Cosmin G.; Saunders, Michael A.: Large-scale optimization with linear equality constraints using reduced compact representation (2022)
  3. Calafiore, Giuseppe C.; Novara, Carlo; Possieri, Corrado: Control analysis and design via randomised coordinate polynomial minimisation (2022)
  4. Deng, Haoyang; Ohtsuka, Toshiyuki: ParNMPC -- a parallel optimisation toolkit for real-time nonlinear model predictive control (2022)
  5. Gade, Jan-Lucas; Thore, Carl-Johan; Stålhand, Jonas: Identification of mechanical properties of arteries with certification of global optimality (2022)
  6. Gao, Pu; Kamiński, Bogumił; MacRury, Calum; Prałat, Paweł: Hamilton cycles in the semi-random graph process (2022)
  7. Hurst, Todd; Rehbock, Volker: Optimizing micro-algae production in a raceway pond with variable depth (2022)
  8. Kirches, Christian; Larson, Jeffrey; Leyffer, Sven; Manns, Paul: Sequential linearization method for bound-constrained mathematical programs with complementarity constraints (2022)
  9. Li, Xuan; Fang, Yu; Li, Minchen; Jiang, Chenfanfu: BFEMP: interpenetration-free MPM-FEM coupling with barrier contact (2022)
  10. Mishra, Prabhat K.; Chowdhary, Girish; Mehta, Prashant G.: Minimum variance constrained estimator (2022)
  11. Adjé, Assalé: Quadratic maximization of reachable values of affine systems with diagonalizable matrix (2021)
  12. Aftalion, Amandine; Trélat, Emmanuel: Pace and motor control optimization for a runner (2021)
  13. Aghaee, Mahya; Hager, William W.: The switch point algorithm (2021)
  14. Ali, Zulfiqar; Ma, Weiyin: Isogeometric collocation method with intuitive derivative constraints for PDE-based analysis-suitable parameterizations (2021)
  15. Almi, Stefano; Belz, Sandro; Micheletti, Stefano; Perotto, Simona: A dimension-reduction model for brittle fractures on thin shells with mesh adaptivity (2021)
  16. Al Sayed, Abdelkader; Bogosel, Beniamin; Henrot, Antoine; Nacry, Florent: Maximization of the Steklov eigenvalues with a diameter constraint (2021)
  17. Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres: PYROBOCOP : Python-based Robotic Control & Optimization Package for Manipulation and Collision Avoidance (2021) arXiv
  18. Bailly, François; Charbonneau, Eve; Danès, Loane; Begon, Mickael: Optimal 3D arm strategies for maximizing twist rotation during somersault of a rigid-body model (2021)
  19. Berahas, Albert S.; Curtis, Frank E.; Robinson, Daniel; Zhou, Baoyu: Sequential quadratic optimization for nonlinear equality constrained stochastic optimization (2021)
  20. Berthold, Timo; Witzig, Jakob: Conflict analysis for MINLP (2021)

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