BASE FUNCTIONALITY. The Gurobi Optimizer includes state-of-the-art linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), and second order cone programming (SOCP) solvers, including mixed-integer programming (MIP) extensions of each. The MIP solvers include shared memory parallelism, capable of simultaneously exploiting any number of processors and cores per processor. The Gurobi Optimizer also includes an Irreducible Infeasible Subsystem (IIS) tool for diagnosing model infeasibility and a performance-tuning tool for automatically identifying beneficial parameter changes, The Gurobi Optimizer is written in C and is accessible from several languages. We provide an interactive Python interface, matrix-oriented interfaces for C, MATLAB, and R, and object-oriented interfaces for C++, Java, .NET, and Python.
Appears in 22 contracts
Sources: End User License Agreement, End User License Agreement, End User License Agreement
BASE FUNCTIONALITY. The Gurobi Optimizer includes state-of-the-art linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), and second order cone programming (SOCP) solvers, including mixed-integer programming (MIP) extensions of each. The MIP solvers include shared memory parallelism, capable of simultaneously exploiting any number of processors and cores per processor. The Gurobi Optimizer also includes an Irreducible Infeasible Subsystem (IIS) tool for diagnosing model infeasibility and a performance-tuning tool for automatically identifying beneficial parameter changes, The Gurobi Optimizer is written in C and is accessible from several languages. We provide an interactive Python interface, matrix-oriented interfaces for C, MATLAB, and R, and object-object- oriented interfaces for C++, Java, .NET, and Python.
Appears in 2 contracts
Sources: End User License Agreement, End User License Agreement
BASE FUNCTIONALITY. The Gurobi Optimizer includes state-of-the-art linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), and second order cone programming (SOCP) solvers, including mixed-integer programming (MIP) extensions of each. The MIP solvers include shared memory parallelism, capable of simultaneously exploiting any number of processors and cores per processor. The Gurobi Optimizer also includes an Irreducible Infeasible Subsystem (IIS) tool for diagnosing model infeasibility and a performance-tuning tool for automatically identifying beneficial parameter changes, The Gurobi Optimizer is written in C and is accessible from several languages. We provide Gurobi provides an interactive Python interface, matrix-oriented interfaces for C, MATLAB, and R, and object-oriented interfaces for C++, Java, .NET, and Python.
Appears in 1 contract
Sources: Cloud License Agreement