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feasopt.py

#!/usr/bin/env python3.11

# Copyright 2024, Gurobi Optimization, LLC

# 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.
#
# We can also use FeasRelax feature to do it. In this example, we
# use minrelax=1, i.e. optimizing the returned model finds a solution
# that minimizes the original objective, but only from among those
# solutions that minimize the sum of the artificial variables.

import sys
import gurobipy as gp

if len(sys.argv) < 2:
    print("Usage: feasopt.py filename")
    sys.exit(0)

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

# create a copy to use FeasRelax feature later

feasmodel1 = feasmodel.copy()

# clear objective

feasmodel.setObjective(0.0)

# add slack variables

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

# optimize modified model

feasmodel.optimize()

feasmodel.write("feasopt.lp")

# use FeasRelax feature

feasmodel1.feasRelaxS(0, True, False, True)

feasmodel1.write("feasopt1.lp")

feasmodel1.optimize()

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Next: fixanddive.py Up: Python Examples Previous: facility.py