# OpenOpt example, similar to gurobi example from
# http://www.gurobi.com/doc/45/quickstart/node11.html,

from FuncDesigner import *
from openopt import MILP
x, y, z = oovars('x y z', domain=bool)
obj = x + y + 2*z
cons = (x + 2*y + 3*z <= 4, x + y >= 1)
startPoint = {x:0, y:0, z:0} # any
p=MILP(obj, startPoint, constraints = cons)
r = p.maximize('glpk', iprint=0) # other OpenOpt MILP solvers: cplex, lpSolve
print(r.xf)
'''
------------------------- OpenOpt 0.37 -------------------------
solver: glpk   problem: unnamed    type: MILP   goal: maximum
 iter   objFunVal   log10(maxResidual)
    0  -0.000e+00               0.00
    1  3.000e+00            -100.00
istop: 1000 (optimal)
Solver:   Time Elapsed = 0.01   CPU Time Elapsed = 0.01
objFunValue: 3 (feasible, MaxResidual = 0)
{x: 1.0, y: 0.0, z: 1.0}
'''