qcp.py
#!/usr/bin/env python3.7 # Copyright 2021, Gurobi Optimization, LLC # This example formulates and solves the following simple QCP model: # maximize x # subject to x + y + z = 1 # x^2 + y^2 <= z^2 (second-order cone) # x^2 <= yz (rotated second-order cone) # x, y, z non-negative import gurobipy as gp from gurobipy import GRB # Create a new model m = gp.Model("qcp") # Create variables x = m.addVar(name="x") y = m.addVar(name="y") z = m.addVar(name="z") # Set objective: x obj = 1.0*x m.setObjective(obj, GRB.MAXIMIZE) # Add constraint: x + y + z = 1 m.addConstr(x + y + z == 1, "c0") # Add second-order cone: x^2 + y^2 <= z^2 m.addConstr(x**2 + y**2 <= z**2, "qc0") # Add rotated cone: x^2 <= yz m.addConstr(x**2 <= y*z, "qc1") m.optimize() for v in m.getVars(): print('%s %g' % (v.varName, v.x)) print('Obj: %g' % obj.getValue())
