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qp.py
#!/usr/bin/env python3.7 # Copyright 2021, 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. import gurobipy as gp from gurobipy import GRB # Create a new model m = gp.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**2 + x*y + y**2 + y*z + z**2 + 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())