python-qsoptex 0.2

Usage

The Python module does not yet expose the full interface of the library but just enough is available to be able to build problems or load problems from a file and solve it. After solving, the values of variables can be obtained, as shown below.

These values will be returned as fractions.Fraction or (if the value is an integer) int. Similarly, when building a problem the parameters can be given as fractions.Fraction or int (or any other numbers.Rational) or anything that can be converted to Fraction using the Fraction constructor (i.e. float, Decimal, etc.).

import qsoptex

p = qsoptex.ExactProblem()

p.add_variable(name='x', objective=2, lower=3.5, upper=17.5)
p.add_variable(name='y', objective=-1, lower=None, upper=2)
p.add_linear_constraint(qsoptex.ConstraintSense.EQUAL, {'x': 1, 'y': 1}, rhs=0)
p.set_objective_sense(qsoptex.ObjectiveSense.MAXIMIZE)

p.set_param(qsoptex.Parameter.SIMPLEX_DISPLAY, 1)
status = p.solve()
if status == qsoptex.SolutionStatus.OPTIMAL:
    print 'Optimal solution'
    print p.get_objective_value()
    print p.get_value('x')

The module is also able to load problems from external files:

p = qsoptex.ExactProblem()
p.read('netlib/cycle.mps', filetype='MPS') # 'LP' is also supported
p.set_param(qsoptex.Parameter.SIMPLEX_DISPLAY, 1)
status = p.solve()

Building

The module requires the QSopt_ex library to be installed. Currently, the modified version at https://github.com/jonls/qsopt-ex is required at version 2.5.10.3 or later.

Use setup.py to build the extension. The setup script is based on setuptools.

$ ./setup install

If GnuMP or QSopt_ex is installed non-standard locations, the include and library paths can be set using the environment variables

• GnuMP: GMP_INCLUDE_DIR and GMP_LIBRARY_DIR

• QSopt_ex: QSOPTEX_INCLUDE_DIR and QSOPTEX_LIBRARY_DIR

For example, if GnuMP is installed in the /opt/local prefix

$ GMP_INCLUDE_DIR=/opt/local/include GMP_LIBRARY_DIR=/opt/local/lib \
        ./setup.py install