def main():
"""
Computes minimal equivalent knapsack inequalities using 'equivknapsack.mod'
"""
kp_cons = [([3, 5], 17, None)]
cons = set()
for k in xrange(len(kp_cons)):
a, a0, bounds = kp_cons[k]
if bounds is None:
bounds = [a0] * len(a)
for i in xrange(len(a)):
bounds[i] = a0 / a[i] if a[i] != 0 else 0
sum_a = sum(x * y for x, y in zip(a, bounds))
aS = abs(2 * a0 + 1 - sum_a)
if a0 < (sum_a - 1) / 2:
a0 += aS
fix_as = 1
else:
if aS > a0:
continue
fix_as = 0
a = a + [aS]
bounds = bounds + [1]
mod_in = "equivknapsack.mod"
mod_out = "tmp/equivknapsack.out.mod"
parser = PyMPL(locals_=locals())
parser.parse(mod_in, mod_out)
lp_out = "tmp/equivknapsack.lp"
glpkutils.mod2lp(mod_out, lp_out)
# exit_code = os.system("glpsol --math {0}".format(mod_out))
# assert exit_code == 0
out, varvalues = VPSolver.script_wsol("vpsolver_glpk.sh", lp_out, verbose=True)
b = [varvalues.get("pi({0})".format(i + 1), 0) for i in xrange(len(a))]
b0 = varvalues.get("pi(0)", 0)
# print a, a0
# print b, b0
if fix_as == 1:
b0 -= b[-1]
b = b[:-1]
else:
b = b[:-1]
if sum(b) != 0:
cons.add((tuple(b), b0, tuple(bounds)))
print "Original knapsack inequalities:"
for a, a0, bounds in sorted(kp_cons, key=lambda x: (x[1], x[0])):
# print a, a0
print " + ".join("{0:2g} x{1:d}".format(a[i], i + 1) for i in xrange(len(a))), "<=", a0
print "Minimal equivalent knapsack inequalities:"
for b, b0, bounds in sorted(cons, key=lambda x: (x[1], x[0])):
# print b, b0
print " + ".join("{0:2g} x{1:d}".format(b[i], i + 1) for i in xrange(len(b))), "<=", b0, bounds[:-1]
def main():
"""Parses 'instance.mod'"""
mod_in = "instance.mod"
mod_out = "tmp/instance.out.mod"
parser = PyMPL()
parser.parse(mod_in, mod_out)
lp_out = "tmp/instance.lp"
glpkutils.mod2lp(mod_out, lp_out, True)
out, varvalues = VPSolver.script_wsol(
"vpsolver_glpk.sh", lp_out, verbose=True
)
sol, varvalues = parser["FLOW"].extract(varvalues, verbose=True)
print
print "sol:", sol
print "varvalues:", [(k, v) for k, v in sorted(varvalues.items())]
print
assert varvalues['Z'] == 21 # check the solution objective value
exit_code = os.system("glpsol --math {0}".format(mod_out))
assert exit_code == 0
def main():
"""Parses 'graph.mod'"""
mod_in = "graph.mod"
mod_out = "tmp/graph.out.mod"
parser = PyMPL()
parser.parse(mod_in, mod_out)
lp_out = "tmp/graph.lp"
glpkutils.mod2lp(mod_out, lp_out)
try:
out, varvalues = VPSolver.script_wsol(
"vpsolver_glpk.sh", lp_out, verbose=True
)
print
print "varvalues:", [(k, v) for k, v in sorted(varvalues.items())]
print
assert varvalues['Z0'] == 9 # check the solution objective value
except Exception as e:
print repr(e)
raise
exit_code = os.system("glpsol --math {0}".format(mod_out))
assert exit_code == 0
def main():
"""
Computes minimal equivalent knapsack inequalities
using 'equivknapsack01.mod'
"""
kp_cons = [
([8, 12, 13, 64, 22, 41], 80),
([8, 12, 13, 75, 22, 41], 96),
([3, 6, 4, 18, 6, 4], 20),
([5, 10, 8, 32, 6, 12], 36),
([5, 13, 8, 42, 6, 20], 44),
([5, 13, 8, 48, 6, 20], 48),
([0, 0, 0, 0, 8, 0], 10),
([3, 0, 4, 0, 8, 0], 18),
([3, 2, 4, 0, 8, 4], 22),
([3, 2, 4, 8, 8, 4], 24),
# ([3, 3, 3, 3, 3, 5, 5, 5], 17),
]
cons = set()
for k in xrange(len(kp_cons)):
a, a0 = kp_cons[k]
aS = abs(2*a0+1-sum(a))
if a0 < (sum(a)-1)/2:
a0 += aS
fix_as = 1
else:
fix_as = 0
if aS > a0:
continue
a = a+[aS]
mod_in = "equivknapsack01.mod"
mod_out = "tmp/equivknapsack01.out.mod"
parser = PyMPL(locals_=locals(), globals_=globals())
parser.parse(mod_in, mod_out)
lp_out = "tmp/equivknapsack01.lp"
glpkutils.mod2lp(mod_out, lp_out)
# exit_code = os.system("glpsol --math {0}".format(mod_out))
# assert exit_code == 0
out, varvalues = VPSolver.script_wsol(
"vpsolver_glpk.sh", lp_out, verbose=False
)
b = [varvalues.get("pi({0})".format(i+1), 0) for i in xrange(len(a))]
b0 = varvalues.get("pi(0)", 0)
# print a, a0
# print b, b0
if fix_as == 1:
b0 -= b[-1]
b = b[:-1]
else:
b = b[:-1]
if sum(b) != 0:
cons.add((tuple(b), b0))
print "Original knapsack inequalities:"
for a, a0 in sorted(kp_cons, key=lambda x: (x[1], x[0])):
# print a, a0
print " + ".join(
"{0:2g} x{1:d}".format(a[i], i+1) for i in xrange(len(a))
), "<=", a0
print "Minimal equivalent knapsack inequalities:"
for b, b0 in sorted(cons, key=lambda x: (x[1], x[0])):
# print b, b0
print " + ".join(
"{0:2g} x{1:d}".format(b[i], i+1) for i in xrange(len(b))
), "<=", b0
