This page gives links to the web pages for all COIN-OR projects. An alphabetical list follows the categorical list below.

Projects by category:

Development tools

  • BuildTools: Tools for managing configuration and compilation of various COIN-OR projects under Linux, Unix, and Cygwin.
  • Coin Bazaar: Small examples and extensions of COIN-OR projects.
  • NLPAPI: A subroutine interface for defining and solving nonlinear programming problems.
  • Pyomo: Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.
  • Test Tools: Python scripts to automatically download, configure, build, test, and install COIN-OR projects.

Documentation

  • CoinEasy: New user information and support, CoinEasy is designed for new users of COIN-OR. The objective is to make it easy to use COIN-OR projects. Different users have different objectives and we provide information on how to get up and running easily depending upon the objective

Graphs

  • Cgc: A collection of network representations and algorithms.
  • GiMPy: a Python library containing pure Python implementations of a variety of graph algorithms with visualizations
  • GrUMPy: a Python library for visualizing various aspects of mathematical programming, including visualizations of the branch-and-cut process, branch-and-bound trees, polyhedra, cutting plane methods, etc.
  • LEMON: A C++ template library aimed at combinatorial optimization tasks, especially those working with graphs and networks.
  • MOCHA: Heuristics and algorithms for multicriteria matroid optimization.

Interfaces

  • AIMMSlinks: Links between the modeling language AIMMS and solvers that are hosted at COIN-OR.
  • CMPL: A mathematical programming language and a system for mathematical programming and optimisation of linear optimisation problems.
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CoinMP: A lightweight API and DLL for CLP, CBC, and CGL.
  • CyLP: a Python interface to Cbc and Clp
  • GAMSlinks: Links between GAMS (General Algebraic Modeling System) and solvers that are hosted at COIN-OR.
  • Optimization Services: A package for representing optimization instances, results, solver options, and communication between clients and solvers in a distributed environment using Web Services.
  • OSI: A uniform API for calling embedded linear and mixed-integer programming solvers.
  • yaposib: a Python interface to linear solvers that use the OSI

Metaheuristics

  • Djinni: A templatized C++ framework with Python bindings for heuristic search.
  • METSlib: An object oriented metaheuristics optimization framework and toolkit in C++.
  • OTS: a framework for constructing tabu search algorithms

Modeling systems

  • CMPL: A mathematical programming language and a system for mathematical programming and optimisation of linear optimisation problems.
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CoinMP: A lightweight API and DLL for CLP, CBC, and CGL.
  • CyLP: a Python interface to Cbc and Clp
  • FLOPC++: An algebraic modeling language embedded in C++.
  • GiMPy: a Python library containing pure Python implementations of a variety of graph algorithms with visualizations
  • pulp-or: A Python library for modeling linear and integer programs.
  • Pyomo: Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.
  • Rehearse: An algebraic modeling library in C++.
  • ROSE: Software for performing symbolic reformulations to Mathematical Programs (MP).
  • yaposib: a Python interface to linear solvers that use the OSI

Optimization convex non-differentiable

  • OBOE: Optimization of convex problems with user-supplied methods delivering key first order information (like support to the feasible set, support to the objective function).
  • RBFOpt: A global derivative-free solver.

Optimization deterministic linear

  • Crème: An implementation of the randomized thermal relaxation method to find a feasible solution of the Maximum Feasible Subsystem problem.

Optimization deterministic linear continuous

  • CLP: A simplex solver.
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CyLP: a Python interface to Cbc and Clp
  • DyLP: An implementation of the dynamic simplex method.
  • FLOPC++: An algebraic modeling language embedded in C++.
  • pulp-or: A Python library for modeling linear and integer programs.
  • Vol: A subgradient algorithm that also computes approximate primal solutions.
  • yaposib: a Python interface to linear solvers that use the OSI

Optimization deterministic linear discrete

  • ABACUS: An LP-based branch-and-cut framework.
  • BCP: A framework for constructing parallel branch-cut-price algorithms for mixed-integer linear programs.
  • CBC: An LP-based branch-and-cut library.
  • Cgl: A library of cutting-plane generators.
  • CHiPPS: A framework for constructing parallel tree search algorithms (includes an LP-based branch-cut-price implementation).
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CyLP: a Python interface to Cbc and Clp
  • DIP: A framework for implementing a variety of decomposition-based branch-and-bound algorithms for solving mixed-integer linear programs.
  • FLOPC++: An algebraic modeling language embedded in C++.
  • pulp-or: A Python library for modeling linear and integer programs.
  • SYMPHONY: A callable library for solving mixed-integer linear programs.
  • VRPH: A library of heuristics for generating solutions to variants of the vehicle routing problem.
  • yaposib: a Python interface to linear solvers that use the OSI

Optimization deterministic nonlinear

  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • DFO: a package for solving general nonlinear optimization problems when derivatives are unavailable
  • filterSD: A library for nonlinear optimization written in Fortran.
  • Ipopt: A solver for general large-scale nonlinear continuous optimization.
  • LaGO: A package for the global optimization of nonconvex mixed-integer nonlinear programs.
  • MC++: A toolkit for bounding factorable functions.
  • MOCHA: Heuristics and algorithms for multicriteria matroid optimization.
  • NLPAPI: A subroutine interface for defining and solving nonlinear programming problems.
  • oBB: Parallel global optimization of Hessian Lipschitz continuous functions.
  • OptiML: interior point, active set method and parametric solvers for support vector machines, solver for the sparse inverse covariance problem
  • qpOASES: An open-source C++ implementation of the recently proposed online active set strategy.

Optimization deterministic nonlinear discrete

  • BONMIN: An experimental open-source C++ code for solving general MINLP (Mixed Integer NonLinear Programming) problems.
  • LaGO: A package for the global optimization of nonconvex mixed-integer nonlinear programs.
  • QAPsolver: Solver for Quadratic Assignment Problem in Fortran.
  • RBFOpt: A global derivative-free solver.

Optimization deterministic nonlinear nonconvex mixed-integer

  • Couenne: A branch-and-bound algorithm for mixed integer nonlinear programming problems.

Optimization deterministic semidefinite continuous

  • CSDP: An interior-point method for semidefinite programming.

Optimization stochastic

  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • FLOPC++: An algebraic modeling language embedded in C++.
  • MOCHA: Heuristics and algorithms for multicriteria matroid optimization.
  • Pyomo: Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.
  • SMI: A stochastic modelling interface for optimization under uncertainty.

Optimization utility

  • ADOL-C: A package for the automatic differentiation of C and C++ programs.
  • Cgc: A collection of network representations and algorithms.
  • CHiPPS: A framework for constructing parallel tree search algorithms (includes an LP-based branch-cut-price implementation).
  • Coin Bazaar: Small examples and extensions of COIN-OR projects.
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CoinMP: A lightweight API and DLL for CLP, CBC, and CGL.
  • CoinUtils: Utilities, data structures, and linear algebra methods for COIN-OR projects.
  • CppAD: A tool for differentiation of C++ functions.
  • LEMON: A C++ template library aimed at combinatorial optimization tasks, especially those working with graphs and networks.
  • Paver: Python scripts to do comparisons of solver performance.
  • PFunc: A lightweight and portable library that provides C and C++ APIs to express task parallelism.
  • Pyomo: Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.
  • RBFOpt: A global derivative-free solver.

Python tools

  • CyLP: a Python interface to Cbc and Clp
  • GiMPy: a Python library containing pure Python implementations of a variety of graph algorithms with visualizations
  • GrUMPy: a Python library for visualizing various aspects of mathematical programming, including visualizations of the branch-and-cut process, branch-and-bound trees, polyhedra, cutting plane methods, etc.
  • Paver: Python scripts to do comparisons of solver performance.
  • yaposib: a Python interface to linear solvers that use the OSI

Stochastic modeling

  • jMarkov: An open-source tool for Markov chain modeling, including finite Markov chains, quasi-birth-and-death processes, phase-type distributions, and Markov decision processes.

Visualization software

  • GiMPy: a Python library containing pure Python implementations of a variety of graph algorithms with visualizations
  • GrUMPy: a Python library for visualizing various aspects of mathematical programming, including visualizations of the branch-and-cut process, branch-and-bound trees, polyhedra, cutting plane methods, etc.

Projects alphabetically:

  • ABACUS: An LP-based branch-and-cut framework.
  • ADOL-C: A package for the automatic differentiation of C and C++ programs.
  • AIMMSlinks: Links between the modeling language AIMMS and solvers that are hosted at COIN-OR.
  • BCP: A framework for constructing parallel branch-cut-price algorithms for mixed-integer linear programs.
  • BONMIN: An experimental open-source C++ code for solving general MINLP (Mixed Integer NonLinear Programming) problems.
  • BuildTools: Tools for managing configuration and compilation of various COIN-OR projects under Linux, Unix, and Cygwin.
  • CBC: An LP-based branch-and-cut library.
  • Cgc: A collection of network representations and algorithms.
  • Cgl: A library of cutting-plane generators.
  • CHiPPS: A framework for constructing parallel tree search algorithms (includes an LP-based branch-cut-price implementation).
  • CLP: A simplex solver.
  • CMPL: A mathematical programming language and a system for mathematical programming and optimisation of linear optimisation problems.
  • Coin Bazaar: Small examples and extensions of COIN-OR projects.
  • CoinBinary: Pre-compiled binary distributions of COIN-OR projects.
  • CoinEasy: New user information and support, CoinEasy is designed for new users of COIN-OR. The objective is to make it easy to use COIN-OR projects. Different users have different objectives and we provide information on how to get up and running easily depending upon the objective
  • CoinMP: A lightweight API and DLL for CLP, CBC, and CGL.
  • CoinUtils: Utilities, data structures, and linear algebra methods for COIN-OR projects.
  • Couenne: A branch-and-bound algorithm for mixed integer nonlinear programming problems.
  • CppAD: A tool for differentiation of C++ functions.
  • Crème: An implementation of the randomized thermal relaxation method to find a feasible solution of the Maximum Feasible Subsystem problem.
  • CSDP: An interior-point method for semidefinite programming.
  • CyLP: a Python interface to Cbc and Clp
  • DFO: a package for solving general nonlinear optimization problems when derivatives are unavailable
  • DIP: A framework for implementing a variety of decomposition-based branch-and-bound algorithms for solving mixed-integer linear programs.
  • Djinni: A templatized C++ framework with Python bindings for heuristic search.
  • DyLP: An implementation of the dynamic simplex method.
  • filterSD: A library for nonlinear optimization written in Fortran.
  • FLOPC++: An algebraic modeling language embedded in C++.
  • GAMSlinks: Links between GAMS (General Algebraic Modeling System) and solvers that are hosted at COIN-OR.
  • GiMPy: a Python library containing pure Python implementations of a variety of graph algorithms with visualizations
  • GrUMPy: a Python library for visualizing various aspects of mathematical programming, including visualizations of the branch-and-cut process, branch-and-bound trees, polyhedra, cutting plane methods, etc.
  • Ipopt: A solver for general large-scale nonlinear continuous optimization.
  • jMarkov: An open-source tool for Markov chain modeling, including finite Markov chains, quasi-birth-and-death processes, phase-type distributions, and Markov decision processes.
  • LaGO: A package for the global optimization of nonconvex mixed-integer nonlinear programs.
  • LEMON: A C++ template library aimed at combinatorial optimization tasks, especially those working with graphs and networks.
  • MC++: A toolkit for bounding factorable functions.
  • METSlib: An object oriented metaheuristics optimization framework and toolkit in C++.
  • MOCHA: Heuristics and algorithms for multicriteria matroid optimization.
  • NLPAPI: A subroutine interface for defining and solving nonlinear programming problems.
  • oBB: Parallel global optimization of Hessian Lipschitz continuous functions.
  • OBOE: Optimization of convex problems with user-supplied methods delivering key first order information (like support to the feasible set, support to the objective function).
  • OptiML: interior point, active set method and parametric solvers for support vector machines, solver for the sparse inverse covariance problem
  • Optimization Services: A package for representing optimization instances, results, solver options, and communication between clients and solvers in a distributed environment using Web Services.
  • OSI: A uniform API for calling embedded linear and mixed-integer programming solvers.
  • OTS: a framework for constructing tabu search algorithms
  • Paver: Python scripts to do comparisons of solver performance.
  • PFunc: A lightweight and portable library that provides C and C++ APIs to express task parallelism.
  • pulp-or: A Python library for modeling linear and integer programs.
  • Pyomo: Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models.
  • QAPsolver: Solver for Quadratic Assignment Problem in Fortran.
  • qpOASES: An open-source C++ implementation of the recently proposed online active set strategy.
  • RBFOpt: A global derivative-free solver.
  • Rehearse: An algebraic modeling library in C++.
  • ROSE: Software for performing symbolic reformulations to Mathematical Programs (MP).
  • SMI: A stochastic modelling interface for optimization under uncertainty.
  • SYMPHONY: A callable library for solving mixed-integer linear programs.
  • Test Tools: Python scripts to automatically download, configure, build, test, and install COIN-OR projects.
  • Vol: A subgradient algorithm that also computes approximate primal solutions.
  • VRPH: A library of heuristics for generating solutions to variants of the vehicle routing problem.
  • yaposib: a Python interface to linear solvers that use the OSI