Other ways of obtaining COIN-OR include downloading it through a number of This is another excellent way to use the COIN-OR Optimization Suite. In particular, there is an image that contains the entire Several Docker images available at Dockerhub. Just doĪt the moment, the first install is quite cumbersome, as it involves installing many dependencies,īut this should be reduced or eliminated, once we move to bottling most projects. Recommended way to install projects on OS X. There are Homebrew recipes for some projects available We are in the process of transitioning to Github Releases. Intel compiler redistributable libraries and the Visual Studio redistributable Libraries compatible with Visual Studio (you will need to install the free On Windows, there are binaries available for some projects on the COIN-OR Various conda recipes are available if you search, e.g., Packages, and will keep this README updated as things progress. We are working on some other better ways of getting binaries, such as conda CppAD (Automatic differentiation in C++)ĭownloading and Installing Pre-built Binariesīinaries for some projects (and their dependencies) are available for download.Dip (Decomposition-based MILP solver framework).BiCePS (Branch, Constrain, and Price Software).Alps (Abstract Library for Parallel Search).

CHiPPS (COIN-OR High Performance Parallel Search framework).

Ipopt (Interior point algorithm for non-linear optimization).

Cbc (COIN-OR branch-and-cut MILP solver).

Vol (approximate LP solver based on Volume Algorithm).

DyLP (LP solver based on dynamic simplex method).

FlopCpp (C++-based algebraic modeling language).

Solvers from the repository of open source software maintained by the COIN-ORįoundation. The COIN-OR Optimization Suite is a collection of interoperable open source Individual projects may have their own documentation. This documentation provides an overview of the projects and how to work with them. Note: If you’ve landed here, you’re probably just getting started with COIN-OR.

Visual studio compiler optimization