qp.py
#!/usr/bin/python
# Copyright 2019, Gurobi Optimization, LLC
# This example formulates and solves the following simple QP model:
# minimize
# x^2 + x*y + y^2 + y*z + z^2 + 2 x
# subject to
# x + 2 y + 3 z >= 4
# x + y >= 1
# x, y, z non-negative
#
# It solves it once as a continuous model, and once as an integer model.
from gurobipy import *
# Create a new model
m = Model("qp")
# Create variables
x = m.addVar(ub=1.0, name="x")
y = m.addVar(ub=1.0, name="y")
z = m.addVar(ub=1.0, name="z")
# Set objective: x^2 + x*y + y^2 + y*z + z^2 + 2 x
obj = x*x + x*y + y*y + y*z + z*z + 2*x
m.setObjective(obj)
# Add constraint: x + 2 y + 3 z <= 4
m.addConstr(x + 2 * y + 3 * z >= 4, "c0")
# Add constraint: x + y >= 1
m.addConstr(x + y >= 1, "c1")
m.optimize()
for v in m.getVars():
print('%s %g' % (v.varName, v.x))
print('Obj: %g' % obj.getValue())
x.vType = GRB.INTEGER
y.vType = GRB.INTEGER
z.vType = GRB.INTEGER
m.optimize()
for v in m.getVars():
print('%s %g' % (v.varName, v.x))
print('Obj: %g' % obj.getValue())
