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.

References in zbMATH (referenced in 288 articles )

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  1. Aswani, Anil; Kaminsky, Philip; Mintz, Yonatan; Flowers, Elena; Fukuoka, Yoshimi: Behavioral modeling in weight loss interventions (2019)
  2. Bagger, Niels-Christian F.; Sørensen, Matias; Stidsen, Thomas R.: Dantzig-Wolfe decomposition of the daily course pattern formulation for curriculum-based course timetabling (2019)
  3. Dursun, Pınar; Taşkın, Z. Caner; Altınel, .I. Kuban: The determination of optimal treatment plans for volumetric modulated arc therapy (VMAT) (2019)
  4. Moon, Han-Bom; Swinarski, David: On the $S_n$-invariant F-conjecture (2019)
  5. Abdallah, L.; Haddou, M.; Migot, T.: Solving absolute value equation using complementarity and smoothing functions (2018)
  6. Angelini, Patrizio; Da Lozzo, Giordano; Di Bartolomeo, Marco; Di Donato, Valentino; Patrignani, Maurizio; Roselli, Vincenzo; Tollis, Ioannis G.: Algorithms and bounds for L-drawings of directed graphs (2018)
  7. Atan, Tankut; Çavdaroğlu, Burak: Minimization of rest mismatches in round Robin tournaments (2018)
  8. Atan, Tankut; Eren, Elif: Optimal project duration for resource leveling (2018)
  9. Bagger, Niels-Christian F.; Sørensen, Matias; Stidsen, Thomas R.: Benders decomposition for curriculum-based course timetabling (2018)
  10. Bamberg, John; Lansdown, Jesse; Lee, Melissa: On $m$-ovoids of regular near polygons (2018)
  11. Bärmann, Andreas; Gellermann, Thorsten; Merkert, Maximilian; Schneider, Oskar: Staircase compatibility and its applications in scheduling and piecewise linearization (2018)
  12. Bertsimas, Dimitris; Gupta, Vishal; Kallus, Nathan: Robust sample average approximation (2018)
  13. Boysen, Nils; Fedtke, Stefan; Weidinger, Felix: Optimizing automated sorting in warehouses: the minimum order spread sequencing problem (2018)
  14. Branda, Martin; Bucher, Max; Červinka, Michal; Schwartz, Alexandra: Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization (2018)
  15. Brandstätter, Christian; Reimann, Marc: The line-haul feeder vehicle routing problem: mathematical model formulation and heuristic approaches (2018)
  16. Burgelman, Jeroen; Vanhoucke, Mario: Maximising the weighted number of activity execution modes in project planning (2018)
  17. Carrasco, Rodrigo A.; Iyengar, Garud; Stein, Cliff: Resource cost aware scheduling (2018)
  18. Carvalho, Desiree M.; Nascimento, Mariá C. V.: A kernel search to the multi-plant capacitated lot sizing problem with setup carry-over (2018)
  19. Cheng, Jianqiang; Chen, Richard Li-Yang; Najm, Habib N.; Pinar, Ali; Safta, Cosmin; Watson, Jean-Paul: Chance-constrained economic dispatch with renewable energy and storage (2018)
  20. Cortés, Pablo; Muñuzuri, Jesús; Berrocal-de-O, Miguel; Domínguez, Ismael: Genetic algorithms to optimize the operating costs of electricity and heating networks in buildings considering distributed energy generation and storage (2018)

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