The Gurobi Optimizer is a state-of-the-art simplex based linear programming (LP) and mixed-integer programming (MIP) solver, built from the ground up to exploit modern multi-core processors. Parallelism is included with every Gurobi license. The Gurobi Parallel MIP Optimizer is deterministic: two separate runs on the same model will produce identical solution paths. Gurobi is also available through several powerful third-party modeling systems including AIMMS, AMPL, FRONTLINE SOLVERS, GAMS, MPL, OptimJ, and TOMLAB. Version 2.0 of the Gurobi Optimizer includes a number of enhancements: * Significant improvements in MIP performance: For difficult models, Gurobi 2.0 is roughly four times as fast as Gurobi 1.1. * Significant improvements in simplex performance: The new dual simplex optimizer is roughly twice as fast as Gurobi 1.1. * Improvements in parallel MIP performance: Gurobi 2.0 extracts more benefit from each additional core in your multi-core system. * MIP IIS (Irreducible Infeasible Subsystem): Gurobi 2.0 can identify the causes of infeasibility in MIP as well as LP models. * MIP node files: Allow you to store MIP nodes on disk and thus solve much larger MIP models. * Cloud computing: Gurobi is now available on-demand via the Amazon Elastic Computing Cloud. * New examples: An extensive new set of examples illustrates key features and uses for Gurobi in all supported languages. * Support for Mac OS X. Version 3.0 of the Gurobi Optimizer contains a number of new features. Users of previous versions may need to make a few minor changes to their existing programs. * Barrier optimizer: The Gurobi Optimizer now includes a parallel barrier optimizer, and a crossover algorithm to transform the barrier solution to an optimal basic solution. Use the LPMethod parameter to select barrier for a continuous model, or the RootMethod parameter to select barrier for the root relaxation of a MIP model. * .NET interface: You can now use the Gurobi Optimizer from Microsoft .NET languages (C#, Visual Basic.NET, etc.). Our .NET interface is object-oriented, and supports the same object model as our C++, Java, and Python interfaces. We've included a complete reference manual, as well as on-line InteliSense help for use within Visual Studio. We've also included a full set of examples in both C# and Visual Basic.NET. * MIP performance: The MIP solver is significantly faster in release 3.0. New features include symmetry handling, improved and additional cutting planes, and additional MIP heuristics. * MIP memory management: The MIP solver manages memory more efficiently. Memory usage is reduced for most models, and node files make more effective use of available memory. * Alternate MIP solutions: You can now retrieve any of the feasible solutions found during the branch-and-cut search. * Presolve: Additional presolve reductions have been added, which help LP and MIP performance. * MPS and LP reader performance improvements: MPS and LP files read as much as 3X faster. * New Mac installer: We've built a new installer for the Mac port. You can now simply double-click on our distributed Gurobi package. * New attributes and parameters: To support the new features in Gurobi 3.0, we have added several new attributes and parameters. You can learn more about these in the Attributes and Parameters sections of the {Gurobi Reference Manual}.