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  2. List of optimization software - Wikipedia

    en.wikipedia.org/wiki/List_of_optimization_software

    MIDACO – a software package for numerical optimization based on evolutionary computing. MINTO – integer programming solver using branch and bound algorithm; freeware for personal use. MOSEK – a large scale optimization software. Solves linear, quadratic, conic and convex nonlinear, continuous and integer optimization.

  3. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    HiGHS is open-source software to solve linear programming (LP), mixed-integer programming (MIP), and convex quadratic programming (QP) models. [1] Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, JavaScript, Fortran, and C#. It has no external dependencies.

  4. Linear programming - Wikipedia

    en.wikipedia.org/wiki/Linear_programming

    Linear programming is a special case of mathematical programming (also known as mathematical optimization ). More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polytope, which is a set defined as the ...

  5. OR-Tools - Wikipedia

    en.wikipedia.org/wiki/OR-Tools

    Google OR-Tools is a free and open-source software suite developed by Google for solving linear programming (LP), mixed integer programming (MIP), constraint programming (CP), vehicle routing (VRP), and related optimization problems. OR-Tools is a set of components written in C++ but provides wrappers for Java, .NET and Python.

  6. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    Interior-point methods (also referred to as barrier methods or IPMs) are algorithms for solving linear and non-linear convex optimization problems. IPMs combine two advantages of previously-known algorithms: Theoretically, their run-time is polynomial β€”in contrast to the simplex method, which has exponential run-time in the worst case.

  7. Big M method - Wikipedia

    en.wikipedia.org/wiki/Big_M_method

    Big M method. In operations research, the Big M method is a method of solving linear programming problems using the simplex algorithm. The Big M method extends the simplex algorithm to problems that contain "greater-than" constraints. It does so by associating the constraints with large negative constants which would not be part of any optimal ...

  8. GLOP - Wikipedia

    en.wikipedia.org/wiki/GLOP

    GLOP (the Google Linear Optimization Package) is Google 's open source linear programming solver, created by Google's Operations Research Team. It is written in C++ and was released to the public as part of Google's OR-Tools software suite in 2014. [1] GLOP uses a revised primal-dual simplex algorithm optimized for sparse matrices. It uses ...

  9. Comparison of optimization software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_optimization...

    Comparison of optimization software. Given a system transforming a set of inputs to output values, described by a mathematical function f, optimization refers to the generation and selection of the best solution from some set of available alternatives, [1] by systematically choosing input values from within an allowed set, computing the value ...