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
References in zbMATH (referenced in 344 articles )
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- Dursun, Pınar; Taşkın, Z. Caner; Altınel, İ. Kuban: The determination of optimal treatment plans for volumetric modulated arc therapy (VMAT) (2019)
- Grimm, Veronika; Kleinert, Thomas; Liers, Frauke; Schmidt, Martin; Zöttl, Gregor: Optimal price zones of electricity markets: a mixed-integer multilevel model and global solution approaches (2019)
- Halder, Abhishek; Geng, Xinbo; Fontes, Fernando A. C. C.; Kumar, P. R.; Xie, Le: Optimal power consumption for demand response of thermostatically controlled loads (2019)
- Hesaraki, Alireza F.; Dellaert, Nico P.; de Kok, Ton: Generating outpatient chemotherapy appointment templates with balanced flowtime and makespan (2019)
- Karimi, Sahar; Ronagh, Pooya: Practical integer-to-binary mapping for quantum annealers (2019)
- Karwowski, Jan; Mańdziuk, Jacek: A Monte Carlo tree search approach to finding efficient patrolling schemes on graphs (2019)
- Krumke, Sven O.; Schmidt, Eva; Streicher, Manuel: Robust multicovers with budgeted uncertainty (2019)
- Liuzzi, G.; Locatelli, M.; Piccialli, Veronica: A new branch-and-bound algorithm for standard quadratic programming problems (2019)