BARON is a computational system for solving nonconvex optimization problems to global optimality. Purely continuous, purely integer, and mixed-integer nonlinear problems can be solved with the software. The Branch And Reduce Optimization Navigator derives its name from its combining constraint propagation, interval analysis, and duality in its reduce arsenal with enhanced branch and bound concepts as it winds its way through the hills and valleys of complex optimization problems in search of global solutions

References in zbMATH (referenced in 311 articles , 2 standard articles )

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  1. Ahmadi, Amir Ali; Hall, Georgina: On the complexity of detecting convexity over a box (2020)
  2. Bosch, P.; Contreras, J. P.; Munizaga-Rosas, J.: Feasibility and cost minimisation for a lithium extraction problem (2020)
  3. Christian D. Hubbs, Hector D. Perez, Owais Sarwar, Nikolaos V. Sahinidis, Ignacio E. Grossmann, John M. Wassick: OR-Gym: A Reinforcement Learning Library for Operations Research Problem (2020) arXiv
  4. Coniglio, Stefano; Gatti, Nicola; Marchesi, Alberto: Computing a pessimistic Stackelberg equilibrium with multiple followers: the mixed-pure case (2020)
  5. Dasdemir, Erdi; Köksalan, Murat; Tezcaner Öztürk, Diclehan: A flexible reference point-based multi-objective evolutionary algorithm: an application to the UAV route planning problem (2020)
  6. Del Pia, Alberto; Khajavirad, Aida; Sahinidis, Nikolaos V.: On the impact of running intersection inequalities for globally solving polynomial optimization problems (2020)
  7. Duarte, Belmiro P. M.; Granjo, José F. O.; Wong, Weng Kee: Optimal exact designs of experiments via mixed integer nonlinear programming (2020)
  8. Enayati, Shakiba; Özaltın, Osman Y.: Optimal influenza vaccine distribution with equity (2020)
  9. Fischetti, Matteo; Monaci, Michele: A branch-and-cut algorithm for mixed-integer bilinear programming (2020)
  10. Gleixner, Ambros; Maher, Stephen J.; Müller, Benjamin; Pedroso, João Pedro: Price-and-verify: a new algorithm for recursive circle packing using Dantzig-Wolfe decomposition (2020)
  11. Goos, P.; Syafitri, U.; Sartono, B.; Vazquez, A. R.: A nonlinear multidimensional knapsack problem in the optimal design of mixture experiments (2020)
  12. Grimstad, Bjarne; Knudsen, Brage R.: Mathematical programming formulations for piecewise polynomial functions (2020)
  13. Jiang, Shan; Fang, Shu-Cherng; Nie, Tiantian; An, Qi: Structured linear reformulation of binary quadratically constrained quadratic programs (2020)
  14. Marandi, Ahmadreza; de Klerk, Etienne; Dahl, Joachim: Solving sparse polynomial optimization problems with chordal structure using the sparse bounded-degree sum-of-squares hierarchy (2020)
  15. Marendet, Antoine; Goldsztejn, Alexandre; Chabert, Gilles; Jermann, Christophe: A standard branch-and-bound approach for nonlinear semi-infinite problems (2020)
  16. Müller, Benjamin; Serrano, Felipe; Gleixner, Ambros: Using two-dimensional projections for stronger separation and propagation of bilinear terms (2020)
  17. Paulavičius, R.; Adjiman, C. S.: New bounding schemes and algorithmic options for the Branch-and-Sandwich algorithm (2020)
  18. Wu, Zeyang; He, Qie: Optimal switching sequence for switched linear systems (2020)
  19. Xia, Wei; Vera, Juan C.; Zuluaga, Luis F.: Globally solving nonconvex quadratic programs via linear integer programming techniques (2020)
  20. Xia, Yong; Wang, Longfei; Wang, Xiaohui: Globally minimizing the sum of a convex-concave fraction and a convex function based on wave-curve bounds (2020)

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