feasopt.py

#!/usr/bin/python

# Copyright 2009, Gurobi Optimization, Inc.

# This example reads a MIP model from a file, adds artificial
# variables to each constraint, and then minimizes the sum of the
# artificial variables.  A solution with objective zero corresponds
# to a feasible solution to the input model.

import sys
from gurobipy import *

if len(sys.argv) < 2:
  print 'Usage: feasopt.py filename'
  quit()

feasmodel = gurobi.read(sys.argv[1])

# clear objective

for v in feasmodel.getVars():
  v.Obj = 0.0

# add slack variables

for c in feasmodel.getConstrs():
  sense = c.Sense
  if sense != '>':
    feasmodel.addVar(obj=1.0, name="ArtN_" + c.ConstrName,
                     column=Column([-1], [c]))
  if sense != '<':
    feasmodel.addVar(obj=1.0, name="ArtP_" + c.ConstrName,
                     column=Column([1], [c]))

feasmodel.update()

# optimize modified model

feasmodel.write('feasopt.lp')

feasmodel.optimize()