sage-numerical-backends-cplex: CPLEX mixed integer linear programming backend for SageMath

CPLEXBackend has previously been available as part of the SageMath source tree, from which it is built as an "optional extension" if the proprietary CPLEX library and header files have been symlinked into $SAGE_LOCAL manually.

Because of the proprietary nature of the CPLEX software, CPLEXBackend is not available in any binary distributions of SageMath.

The present standalone Python package sage-numerical-backends-cplex has been created from the SageMath sources, version 9.0.beta10. It can be installed on top of various Sage installations using pip, including older versions of Sage such as 8.1 (as shipped by Ubuntu bionic 18.04LTS).

Installation

CPLEX is proprietary software. It is available for free for researchers and students through IBM's Academic Initiative.

Install CPLEX according to the instructions on the website.

To prepare installation of sage-numerical-backends-cplex, find the installation directory of your ILOG CPLEX Studio installation, which contains subdirectories cplex, doc, opl, etc. Set the environment variable CPLEX_HOME to this directory; for example using the following shell command (on macOS):

    $ export CPLEX_HOME=/Applications/CPLEX_Studio1210

or (on Linux):

    $ export CPLEX_HOME=/opt/ibm/ILOG/CPLEX_Studio1210

Now verify that the CPLEX binary that you will find in the subdirectory cplex/bin/ARCH_OS starts correctly, for example::

$ $CPLEX_HOME/cplex/bin/x86-64_osx/cplex
Welcome to IBM(R) ILOG(R) CPLEX(R) Interactive Optimizer...

(Alternatively, set compiler/linker flags (or use symbolic links) so that "cplex.h" and "libcplex.so" can be found.)

Now install this package from PyPI using

$ sage -python -m pip install sage-numerical-backends-cplex

or from a checked out source tree using

$ sage -python -m pip install .

or from GitHub using

$ sage -python -m pip install git+https://github.com/mkoeppe/sage-numerical-backends-cplex

(See build.yml in the related package sage-numerical-backends-coin package for details about package prerequisites on various systems.)

Using this package

To obtain a solver (backend) instance:

sage: from sage_numerical_backends_cplex.cplex_backend import CPLEXBackend
sage: CPLEXBackend()
<sage_numerical_backends_cplex.cplex_backend.CPLEXBackend object at 0x7fb72c2c7528>

Equivalently:

sage: from sage_numerical_backends_cplex.cplex_backend import CPLEXBackend
sage: from sage.numerical.backends.generic_backend import get_solver
sage: get_solver(solver=CPLEXBackend)
<sage_numerical_backends_cplex.cplex_backend.CPLEXBackend object at 0x7fe21ffbe2b8>

To use this solver (backend) with MixedIntegerLinearProgram:

sage: from sage_numerical_backends_cplex.cplex_backend import CPLEXBackend
sage: M = MixedIntegerLinearProgram(solver=CPLEXBackend)
sage: M.get_backend()
<sage_numerical_backends_cplex.cplex_backend.CPLEXBackend object at 0x7fb72c2c7868>

Setting it as the default backend for MixedIntegerLinearProgram, as of SageMath 9.0.beta10, requires some trickery:

sage: import sage_numerical_backends_cplex.cplex_backend as cplex_backend, sage.numerical.backends as backends, sys
sage: sys.modules['sage.numerical.backends.cplex_backend'] = backends.cplex_backend = cplex_backend
sage: default_mip_solver('CPLEX')

To patch this in permanently (at your own risk):

$ sage -c 'import os; import sage.numerical.backends as dm; import sage_numerical_backends_cplex.cplex_backend as sm; s = sm.__file__; f = os.path.basename(s); d = os.path.join(dm.__path__[0], f); (os.path.exists(d) or os.path.lexists(d)) and os.remove(d); os.symlink(s, d);'

Or use the script patch_into_sage_module.py in the source distribution that does the same:

$ sage -c 'load("patch_into_sage_module.py")'
Success: Patched in the module as sage.numerical.backends.cplex_backend

Verify with check_get_solver_with_name.py that the patching script has worked:

$ sage -c 'load("check_get_solver_with_name.py")'
Success: get_solver(solver='cplex') gives <sage_numerical_backends_cplex.cplex_backend.CPLEXBackend object at 0x7f8f20218528>