Created
July 5, 2021 13:02
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Getting started with OR tools
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# Getting started: | |
# Python3 installation: python -m pip install --upgrade --user ortools | |
# | |
# Optimisation with the OR tool can be done in 5 steps: | |
# Creating a solver | |
# Creating a variable (x, y, … etc.) | |
# Creating linear constraints | |
# Creating an objective function | |
# Run the solver | |
# | |
# E.g: max z = 8x1 + 11x2 + 6x3 + 4x4 | |
# Such that: | |
# 5x1 + 7x2 + 0x3 + 3x4 <= 14 | |
# 8x1 + 0x2 + 4x3 + 4x4 <= 12 | |
# 2x1 + 10x2 + 6x3 + 4x4 <= 15 | |
# | |
# x1, x2, x3, x4 belongs to [0, 1] | |
#!/usr/bin/python3 | |
from ortools.linear_solver import pywraplp | |
# Create the linear solver with the GLOP backend. | |
solver = pywraplp.Solver.CreateSolver('GLOP') | |
# Create the variables x1 to x4. | |
x1 = solver.NumVar(0, 1, 'x1') | |
x2 = solver.NumVar(0, 1, 'x2') | |
x3 = solver.NumVar(0, 1, 'x3') | |
x4 = solver.NumVar(0, 1, 'x4') | |
print('Number of variables =', solver.NumVariables()) | |
# Add a linear constraint, 5x1 + 7x2 + 0x3 + 3x4 <= 14. | |
ct1 = solver.Constraint(0, 14, 'ct1') | |
ct1.SetCoefficient(x1, 5) | |
ct1.SetCoefficient(x2, 7) | |
ct1.SetCoefficient(x3, 0) | |
ct1.SetCoefficient(x4, 3) | |
# Add a linear constraint, 8x1 + 0x2 + 4x3 + 4x4 <= 12. | |
ct2 = solver.Constraint(0, 12, 'ct2') | |
ct2.SetCoefficient(x1, 8) | |
ct2.SetCoefficient(x2, 0) | |
ct2.SetCoefficient(x3, 4) | |
ct2.SetCoefficient(x4, 4) | |
# Add a linear constraint, 2x1 + 10x2 + 6x3 + 4x4 <= 15. | |
ct3 = solver.Constraint(0, 15, 'ct3') | |
ct3.SetCoefficient(x1, 2) | |
ct3.SetCoefficient(x2, 10) | |
ct3.SetCoefficient(x3, 6) | |
ct3.SetCoefficient(x4, 4) | |
print('Number of constraints =', solver.NumConstraints()) | |
# Create the objective function, 8x1 + 11x2 + 6x3 + 4x4. | |
objective = solver.Objective() | |
objective.SetCoefficient(x1, 8) | |
objective.SetCoefficient(x2, 11) | |
objective.SetCoefficient(x3, 6) | |
objective.SetCoefficient(x4, 4) | |
objective.SetMaximization() | |
solver.Solve() | |
print('Solution:') | |
print('Objective value =', objective.Value()) | |
print('x1 =', x1.solution_value()) | |
print('x2 =', x2.solution_value()) | |
print('x3 =', x3.solution_value()) | |
print('x4 =', x4.solution_value()) |
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A Binary Linear Programming Optimization script.