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The use of optimization software requires that the function f is defined in a suitable programming language and connected at compilation or run time to the optimization software. The optimization software will deliver input values in A , the software module realizing f will deliver the computed value f ( x ) and, in some cases, additional ...
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, R, JavaScript, Fortran, and C#. It has no external dependencies.
Boost Software License High-performance C++ linear algebra library based on Generic programming: NAG Numerical Library: The Numerical Algorithms Group: C, Fortran 1971 many components Non-free Proprietary General purpose numerical analysis library. NMath: CenterSpace Software: C# 2003 7.1 / 12.2019 Non-free Proprietary
Automatically Tuned Linear Algebra Software (ATLAS) is a software library for linear algebra. It provides a mature open source implementation of BLAS APIs for C and FORTRAN 77 . ATLAS is often recommended as a way to automatically generate an optimized BLAS library.
The optimization software will deliver input values in A, the software module realizing f will deliver the computed value f(x). In this manner, a clear separation of concerns is obtained: different optimization software modules can be easily tested on the same function f, or a given optimization software can be used for different functions f.
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.
LAPACK ("Linear Algebra Package") is a standard software library for numerical linear algebra. It provides routines for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition.
For linear programs, Xpress further implements a primal-dual hybrid gradient algorithm. All mixed integer programming variants as well as nonconvex continuous problems are solved by a combination of the branch and bound method and the cutting-plane method. Infeasible problems can be analyzed via the IIS (irreducible infeasible subset) method ...