Gurobi

GUROBI OPTIMIZER: State of the Art Mathematical Programming Solver. The Gurobi Optimizer is a state-of-the-art solver for mathematical programming. It includes the following solvers: linear programming solver (LP), quadratic programming solver (QP), quadratically constrained programming solver (QCP), mixed-integer linear programming solver (MILP), mixed-integer quadratic programming solver (MIQP), and mixed-integer quadratically constrained programming solver (MIQCP). The solvers in the Gurobi Optimizer were designed from the ground up to exploit modern architectures and multi-core processors, using the most advanced implementations of the latest algorithms. To help set you up for success, the Gurobi Optimizer goes beyond fast and reliable solution performance to provide a broad range of interfaces, access to industry-standard modeling languages, flexible licensing together with transparent pricing, and outstanding, easy to reach, support.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 501 articles )

Showing results 1 to 20 of 501.
Sorted by year (citations)

1 2 3 ... 24 25 26 next

  1. Ahmadi, Amir Ali; Hall, Georgina: On the complexity of detecting convexity over a box (2020)
  2. Almeida Guimarães, Dilson; Salles da Cunha, Alexandre; Pereira, Dilson Lucas: Semidefinite programming lower bounds and branch-and-bound algorithms for the quadratic minimum spanning tree problem (2020)
  3. Arana-Jiménez, Manuel; Blanco, Víctor; Fernández, Elena: On the fuzzy maximal covering location problem (2020)
  4. Araujo, Janniele A. S.; Santos, Haroldo G.; Gendron, Bernard; Jena, Sanjay Dominik; Brito, Samuel S.; Souza, Danilo S.: Strong bounds for resource constrained project scheduling: preprocessing and cutting planes (2020)
  5. Aslan, Ayse; Bakir, Ilke; Vis, Iris F. A.: A dynamic Thompson sampling hyper-heuristic framework for learning activity planning in personalized learning (2020)
  6. Bärmann, Andreas; Gemander, Patrick; Merkert, Maximilian: The clique problem with multiple-choice constraints under a cycle-free dependency graph (2020)
  7. Bayless, Sam; Kodirov, Nodir; Iqbal, Syed M.; Beschastnikh, Ivan; Hoos, Holger H.; Hu, Alan J.: Scalable constraint-based virtual data center allocation (2020)
  8. Ben Hermans, Andreas Themelis, Panagiotis Patrinos: QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs (2020) arXiv
  9. Bereg, Sergey; Mojica, Luis Gerardo; Morales, Linda; Sudborough, Hal: Constructing permutation arrays using partition and extension (2020)
  10. Beresnev, Vladimir; Melnikov, Andrey: (\varepsilon)-Constraint method for bi-objective competitive facility location problem with uncertain demand scenario (2020)
  11. Bertsimas, Dimitris; Dunning, Iain: Relative robust and adaptive optimization (2020)
  12. Bertsimas, Dimitris; Lamperski, Jourdain; Pauphilet, Jean: Certifiably optimal sparse inverse covariance estimation (2020)
  13. Bhuiyan, Tanveer Hossain; Medal, Hugh R.; Harun, Sarah: A stochastic programming model with endogenous and exogenous uncertainty for reliable network design under random disruption (2020)
  14. Borgwardt, Steffen; Viss, Charles: An implementation of steepest-descent augmentation for linear programs (2020)
  15. Brantley, Halley L.; Guinness, Joseph; Chi, Eric C.: Baseline drift estimation for air quality data using quantile trend filtering (2020)
  16. Burlacu, Robert; Geißler, Björn; Schewe, Lars: Solving mixed-integer nonlinear programmes using adaptively refined mixed-integer linear programmes (2020)
  17. Çavdaroğlu, Burak; Atan, Tankut: Determining matchdays in sports league schedules to minimize rest differences (2020)
  18. Cea, Sebastián; Durán, Guillermo; Guajardo, Mario; Sauré, Denis; Siebert, Joaquín; Zamorano, Gonzalo: An analytics approach to the FIFA ranking procedure and the world cup final draw (2020)
  19. Chen, Qian Matteo; Finzi, Alberto; Mancini, Toni; Melatti, Igor; Tronci, Enrico: MILP, pseudo-Boolean, and OMT solvers for optimal fault-tolerant placements of relay nodes in mission critical wireless networks (2020)
  20. 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

1 2 3 ... 24 25 26 next