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.

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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. Gao, Pu; Kamiński, Bogumił; MacRury, Calum; Prałat, Paweł: Hamilton cycles in the semi-random graph process (2022)
  3. Adjé, Assalé: Quadratic maximization of reachable values of affine systems with diagonalizable matrix (2021)
  4. Aftalion, Amandine; Trélat, Emmanuel: Pace and motor control optimization for a runner (2021)
  5. Aghaee, Mahya; Hager, William W.: The switch point algorithm (2021)
  6. Ali, Zulfiqar; Ma, Weiyin: Isogeometric collocation method with intuitive derivative constraints for PDE-based analysis-suitable parameterizations (2021)
  7. Al Sayed, Abdelkader; Bogosel, Beniamin; Henrot, Antoine; Nacry, Florent: Maximization of the Steklov eigenvalues with a diameter constraint (2021)
  8. Arvind U. Raghunathan, Devesh K. Jha, Diego Romeres: PYROBOCOP : Python-based Robotic Control & Optimization Package for Manipulation and Collision Avoidance (2021) arXiv
  9. Bailly, François; Charbonneau, Eve; Danès, Loane; Begon, Mickael: Optimal 3D arm strategies for maximizing twist rotation during somersault of a rigid-body model (2021)
  10. Berahas, Albert S.; Curtis, Frank E.; Robinson, Daniel; Zhou, Baoyu: Sequential quadratic optimization for nonlinear equality constrained stochastic optimization (2021)
  11. Berthold, Timo; Witzig, Jakob: Conflict analysis for MINLP (2021)
  12. Birgin, E. G.; Gardenghi, J. L.; Martínez, J. M.; Santos, S. A.: On the solution of linearly constrained optimization problems by means of barrier algorithms (2021)
  13. Bollhöfer, Matthias; Schenk, Olaf; Verbosio, Fabio: A high performance level-block approximate LU factorization preconditioner algorithm (2021)
  14. Bonart, Henning; Kahle, Christian: Optimal control of sliding droplets using the contact angle distribution (2021)
  15. Borges, Pedro; Sagastizábal, Claudia; Solodov, Mikhail: Decomposition algorithms for some deterministic and two-stage stochastic single-leader multi-follower games (2021)
  16. Borges, Pedro; Sagastizábal, Claudia; Solodov, Mikhail: A regularized smoothing method for fully parameterized convex problems with applications to convex and nonconvex two-stage stochastic programming (2021)
  17. Botkin, Nikolai; Turova, Varvara; Hosseini, Barzin; Diepolder, Johannes; Holzapfel, Florian: Tracking aircraft trajectories in the presence of wind disturbances (2021)
  18. Brust, Johannes J.; Di, Zichao (Wendy); Leyffer, Sven; Petra, Cosmin G.: Compact representations of structured BFGS matrices (2021)
  19. Cerulli, Martina; D’Ambrosio, Claudia; Liberti, Leo; Pelegrín, Mercedes: Detecting and solving aircraft conflicts using bilevel programming (2021)
  20. Dandurand, Brian C.; Kim, Kibaek; Leyffer, Sven: A bilevel approach for identifying the worst contingencies for nonconvex alternating current power systems (2021)

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