Source code for naginterfaces.library.examples.mip.ilp_dense_ex

#!/usr/bin/env python3
"``naginterfaces.library.mip.ilp_dense`` Python Example."

# NAG Copyright 2017-2019.

# pylint: disable=invalid-name,too-many-locals

import numpy as np

from naginterfaces.library import mip, opt

def main():
    """
    Example for :func:`naginterfaces.library.mip.ilp_dense`.

    Dense integer LP.

    >>> main()
    naginterfaces.library.mip.ilp_dense Python Example Results.
    Solve an ILP problem.
    Final objective value is -1.4000000e+01
    """

    print('naginterfaces.library.mip.ilp_dense Python Example Results.')
    print('Solve an ILP problem.')

    # Initialize the solver:
    comm = opt.nlp1_init('opt.lp_solve')
    # The initial guess:
    x = [1., 1.]
    # Unbounded iteration limit:
    itmax = 0
    # No diagnostic output:
    msglvl = 0
    # The general constraints:
    a = np.array(
        [
            [2., 5.],
            [2., -2.],
            [3., 2.],
        ]
    )
    # The infinite bound size:
    bigbnd = 1.e20
    # The bounds:
    bl = [0., 0., -bigbnd, -bigbnd, 5.]
    bu = [bigbnd, bigbnd, 15., 5., bigbnd]
    # The integer variables:
    intvar = [1, 1]
    # The objective coefficients:
    cvec = [-3., -4.]
    # No limit on the node search:
    maxnod = 0
    # No early termination:
    intfst = 0
    # Maximum depth:
    maxdpt = 4
    # Use computed default tolerances:
    toliv = 0.
    tolfes = 0.

    objmip = mip.ilp_dense(
        itmax, msglvl, a, bl, bu, intvar, cvec,
        maxnod, intfst, toliv, tolfes, bigbnd, x, comm, maxdpt=maxdpt,
    ).objmip

    print('Final objective value is {:.7e}'.format(objmip))

if __name__ == '__main__':
    import doctest
    import sys
    sys.exit(
        doctest.testmod(
            None, verbose=True, report=False,
            optionflags=doctest.REPORT_NDIFF,
        ).failed
    )