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Model and Solve Comple Problems with Solver Foundation

Microsoft Solver Foundation is an extensible framework that helps you model and solve complex problems by:

  • Modeling and solving scenarios by using constraints, goals, and data.
  • Programming in the Optimization Modeling Language (OML), in C# imperatively, in F# functionally, or in any .NET Framework language.
  • Integrating third-party solvers, such as Gurobi, Mosek™, FICO™ Xpress, LINDO, CPLEX®, and lp_solve.
  • Using familiar interfaces in Microsoft Office Excel and SharePoint to create and solve models.

    Solver Foundation Services (SFS) can automatically analyze models and determine which solver is most appropriate. If you are an advanced modeler, you can choose specific solvers and solver attributes. While solving the models, SFS manages all threading, many-core, synchronization, scheduling, and model execution issues. When finished, SFS produces reports about solver behavior and results, and provides additional information about solutions, including sensitivity. Finally, SFS allows LINQ data binding of model parameters and delivery of results in multiple formats.

    Solver Foundation allows new or existing third-party solvers to plug into the SFS directly, avoiding the need to learn a new modeling language or the significant overhead in managing solver specific solutions. These solvers include numerical, symbolic, and search algorithms that you can use in your models. There is a collection of certified partner wrappers for Gurobi, Mosek ™, FICO™ Xpress, and LINDO, as well as reference wrapper source code for CPLEX ® and lp_solve.
    The Solver Foundation’s intrinsic solvers are written in managed code covering several families of numerical and symbolic programming:

    • Revised Simplex Linear Programming (Primal and Dual Simplex)
    • Interior Point Method Linear, Quadratic, and Second Ordered Conic Programming
    • Constraint Programming with Exhaustive Tree Search, Local Search, and Metaheuristic Techniques
    • Stochastic Programming
    • Compact, Quasi-Newton (L-BFGS), Unconstrained Nonlinear Programming
    • Mixed Integer Programming
    • In Solver Foundation version 2.0, we included the Gurobi Optimization MIP solver as our default MIP solver.

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