Clp

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Clp (Coin-or linear programming) is an open-source linear programming solver. It is primarily meant to be used as a callable library, but a basic, stand-alone executable version is also available. It is designed to find solutions of mathematical optimization problems of the form

minimize c'x such that lhs ≤ Ax ≤ rhs and lb ≤ x ≤ ub

CLP includes primal and dual Simplex solvers. Both dual and primal algorithms can use matrix storage methods provided by the user (0-1 and network matrices are already supported in addition to the default sparse matrix). The dual algorithm has Dantzig and Steepest edge row pivot choices; new ones may be provided by the user. The same is true for the column pivot choice of the primal algorithm. The primal can also use a non linear cost which should work for piecewise linear convex functions. CLP also includes a barrier method for solving LPs.

Clp is written in C++ and is released as open source under the Eclipse Public License 2.0.

It is distributed under the auspices of the COIN-OR Foundation.

The Clp development site is https://github.com/coin-or/Clp.

CITE

Code:

CURRENT BUILD STATUS

DOWNLOAD

What follows is a quick start guide for obtaining or building Clp on common platforms. More detailed information is available here.

Docker image

There is a Docker image that provides Clp, as well as other projects in the COIN-OR Optimization Suite here

Binaries

For newer releases, binaries will be made available as assets attached to releases in Github here. Older binaries are archived as part of Clp here.

• Linux (see https://repology.org/project/coin-or-clp/versions for a complete listing):

  • arch:

    $ sudo pacman -S  coin-or-clp
    

  • Debian/Ubuntu:

    $ sudo apt-get install  coinor-clp coinor-libclp-dev
    

  • Fedora/Redhat/CentOS:

    $ sudo yum install  coin-or-Clp coin-or-Clp-devel
    

  • freebsd:

    $ sudo pkg install math/clp
    

  • linuxbrew:

    $ brew install clp
    

• Windows: The easiest way to get Clp on Windows is to download an archive as described above.

• Mac OS X: The easiest way to get Clp on Mac OS X is through Homebrew.

  $ brew tap coin-or-tools/coinor
  $ brew install coin-or-tools/coinor/clp
  

• conda (cross-platform, no Windows for now):

  $ conda install coin-or-clp
  

Due to license incompatibilities, pre-compiled binaries lack some functionality. If binaries are not available for your platform for the latest version and you would like to request them to be built and posted, feel free to let us know on the mailing list.

Source

Source code can be obtained either by

• Downloading a snapshot of the source code for the latest release version of Clp from the releases page,
• Cloning this repository from Github, or
• Using the coinbrew script to get the project and all dependencies (recommended, see below).

Dependencies

Clp has a number of dependencies, which are detailed in config.yml. Dependencies on other COIN-OR projects are automatically downloaded when obtaining the source with coinbrew. For some of the remaining third-party dependencies, automatic download scripts and build wrappers are provided (and will also be automatically run for required and recommended dependencies), while other libraries that are aeasy to obtain must be installed using an appropriate package manager (or may come with your OS by default).

BUILDING from source

These quick start instructions assume you are in a bash shell.

Using coinbrew

To download and build Clp from source, execute the following on the command line.

wget https://raw.githubusercontent.com/coin-or/coinbrew/master/coinbrew
chmod u+x coinbrew
./coinbrew fetch Clp@master
./coinbrew build Clp

For more detailed instructions on coinbrew, see https://coin-or.github.io/coinbrew. The coinbrew script will fetch the additional projects specified in the Dependencies section of config.yml.

Without coinbrew (Expert users)

• Download the source code, e.g., by cloning the git repo https://github.com/coin-or/Clp
• Download and install the source code for the dependencies listed in config.yml
• Build the code as follows (make sure to set PKG_CONFIG_PTH to install directory for dependencies).

./configure -C
make
make test
make install

With Microsoft Visual Studio

For Microsoft Visual C++ users, there are project files for version 10 available in the MSVisualStudio directory. First, obtain the source code using either a Windows git client or download a snapshot. In MSVC++ Version 10, open the solution file (this should be converted to whatever version of MSVC+ you are using) and build the Clp project. The code should build out of the box with default settings.

It is also possible to build Clp with the Visual Studio compiler from the command line using the procedure for Unix-like environments, using the Msys2 shell or CYGWIN. This is the recommended and best-supported way of building Clp in Windows from source. To do so, make sure the cl compiler is in your path and add --enable-msvc to build command of coinbrew.

Quick start

Running clp gives you some hints. It can do a unit test (clp -unitTest) and solve netlib problems (-netlib or -netlibp using primal). It can also solve problems and set tolerances etc. Just do

clp 

and then try ? or setting various stuff.

clp filename                #read file, do presolve and dual algorithm
clp filename -primalsimplex #use primal instead

On Linux, clp can do file completion and line editing if it can find the history, readline, and termcap packages when building.

If you want to stress the code, you can set various stuff, e.g., dantzig pricing and then go into netlib testing. It is not guaranteed that it will solve all netlib instances if you get too creative. For instance using presolve makes netlib solve faster - but pilot87 prefers a large infeasibility weight. So

clp -presolve on -dualbound 1.0e10 -netlib

works well.

There are examples in examples. To create an executable, build with coinbrew as above and then do

cd build/Cbc/master/examples
make DRIVER=minimum #build the driver minimum.cpp

or whichever driver you want. A list is in Makefile. Three useful samples are:

• minimum.cpp This is the simplest possible program to read an mps file.

• defaults.cpp. This does not do much more, but it does it in much more complicated way by specifically setting defaults so it does give more useful information. It also prints a solution in a format similar to that of MPSX.

• presolve.cpp This is a good driver for larger problems.

Other ones can get complicated so start simple and work your way up.

Doxygen Documentation

If you have Doxygen available, you can build a HTML documentation by typing

make doxygen-docs

in the build directory. If Clp was built via coinbrew, then the build directory will be ./build/Clp/master by default. The doxygen documentation main file is found at <build-dir>/doxydoc/html/index.html.

If you don't have doxygen installed locally, you can use also find the documentation here.

Project Links

Help:

• Code of Conduct
• Discussion forum
• Report a bug

Documentation:

• Doxygen-generated html documentation
• Source code examples
• User's Guide (from 2004)

Interfaces:

• Matlab Interface + Windows x86 & x64 Interface Binaries (OPTI Toolbox)
• Julia interface
• R and CLP - a quick start
• Java and CLP - performs well