lpmod.py

#!/usr/bin/env python3.11

# Copyright 2025, Gurobi Optimization, LLC

# This example reads an LP model from a file and solves it.
# If the model can be solved, then it finds the smallest positive variable,
# sets its upper bound to zero, and resolves the model two ways:
# first with an advanced start, then without an advanced start
# (i.e. 'from scratch').

import sys
import gurobipy as gp
from gurobipy import GRB

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

# Read model and determine whether it is an LP

model = gp.read(sys.argv[1])
if model.IsMIP == 1:
    print("The model is not a linear program")
    sys.exit(1)

model.optimize()

status = model.Status

if status == GRB.INF_OR_UNBD or status == GRB.INFEASIBLE or status == GRB.UNBOUNDED:
    print("The model cannot be solved because it is infeasible or unbounded")
    sys.exit(1)

if status != GRB.OPTIMAL:
    print(f"Optimization was stopped with status {status}")
    sys.exit(0)

# Find the smallest variable value
minVal = GRB.INFINITY
for v in model.getVars():
    if v.X > 0.0001 and v.X < minVal and v.LB == 0.0:
        minVal = v.X
        minVar = v

print(f"\n*** Setting {minVar.VarName} from {minVal:g} to zero ***\n")
minVar.UB = 0.0

# Solve from this starting point
model.optimize()

# Save iteration & time info
warmCount = model.IterCount
warmTime = model.Runtime

# Reset the model and resolve
print("\n*** Resetting and solving without an advanced start ***\n")
model.reset()
model.optimize()

coldCount = model.IterCount
coldTime = model.Runtime

print("")
print(f"*** Warm start: {warmCount:g} iterations, {warmTime:g} seconds")
print(f"*** Cold start: {coldCount:g} iterations, {coldTime:g} seconds")