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  2. SU2 code - Wikipedia

    en.wikipedia.org/wiki/SU2_code

    New in-memory Python wrapping of SU2 using SWIG with accompanying high-level API. Class enhancements for multiphysics applications, including interpolation and transfer. Free-form deformation (FFD) extensions, including Bézier curves and improved usability. Reorganization of the incompressible solver for future expansion.

  3. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more. [17] SciPy, [18] [19] [20] a large BSD-licensed library of scientific tools. De facto standard for scientific computations in Python.

  4. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    The SciPy scientific library, for instance, uses HiGHS as its LP solver [13] from release 1.6.0 [14] and the HiGHS MIP solver for discrete optimization from release 1.9.0. [15] As well as offering an interface to HiGHS, the JuMP modelling language for Julia [ 16 ] also describes the specific use of HiGHS in its user documentation. [ 17 ]

  5. OR-Tools - Wikipedia

    en.wikipedia.org/wiki/OR-Tools

    OR-Tools was created by Laurent Perron in 2011. [5]In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools. [1]The CP-SAT solver [6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge, [7] an international constraint programming competition.

  6. Z3 Theorem Prover - Wikipedia

    en.wikipedia.org/wiki/Z3_Theorem_Prover

    The solver can be built using Visual Studio, a makefile or using CMake and runs on Windows, FreeBSD, Linux, and macOS. The default input format for Z3 is SMTLIB2 . It also has officially supported bindings for several programming languages , including C , C++ , Python , .NET , Java , and OCaml .

  7. Gekko (optimization software) - Wikipedia

    en.wikipedia.org/wiki/Gekko_(optimization_software)

    GEKKO works on all platforms and with Python 2.7 and 3+. By default, the problem is sent to a public server where the solution is computed and returned to Python. There are Windows, MacOS, Linux, and ARM (Raspberry Pi) processor options to solve without an Internet connection.

  8. Couenne - Wikipedia

    en.wikipedia.org/wiki/Couenne

    github.com /coin-or /Couenne Convex Over and Under ENvelopes for Nonlinear Estimation ( Couenne ) is an open-source library for solving global optimization problems, also termed mixed integer nonlinear optimization problems. [ 1 ]

  9. SageMath - Wikipedia

    en.wikipedia.org/wiki/SageMath

    Both binaries and source code are available for SageMath from the download page. If SageMath is built from source code, many of the included libraries such as OpenBLAS, FLINT, GAP (computer algebra system), and NTL will be tuned and optimized for that computer, taking into account the number of processors, the size of their caches, whether there is hardware support for SSE instructions, etc.