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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.
Matrix Toolkit Java is a linear algebra library based on BLAS and LAPACK. ojAlgo is an open source Java library for mathematics, linear algebra and optimisation. exp4j is a small Java library for evaluation of mathematical expressions. SuanShu is an open-source Java math library. It supports numerical analysis, statistics and optimization.
An open source computational geometry package which includes a quadratic programming solver. CPLEX: Popular solver with an API (C, C++, Java, .Net, Python, Matlab and R). Free for academics. Excel Solver Function: A nonlinear solver adjusted to spreadsheets in which function evaluations are based on the recalculating cells.
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. [5]
Java 8.0.0.Final / November 2020 Yes Yes ASL (open source) Lightweight optimization solver in Java, with optional integration modules for JPA-Hibernate, Quarkus, Spring, Jackson, JAXB, etc. Works on Kotlin and Scala too. SciPy: Python 0.13.1 / November 2013 Yes Yes BSD General purpose numerical and scientific computing library for Python.
OptimJ – Java-based modelling language; the free edition includes support for lp_solve, GLPK and LP or MPS file formats. PottersWheel – parameter estimation in ordinary differential equations (free MATLAB toolbox for academic use). Pyomo – collection of Python software packages for formulating optimization models.
The following tables provide a comparison of computer algebra systems (CAS). [1] [2] [3] A CAS is a package comprising a set of algorithms for performing symbolic manipulations on algebraic objects, a language to implement them, and an environment in which to use the language.
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.