Can I print the linear programming sensitivity analysis report using google or-tools?

Question

One can solve the linear programs using google or-tools with GLOP solver. I wonder if there is a way to print the sensitivity report (like shadow prices etc.).

Answer 1

Here is a straightforward conversion of Python PuLP code from https://machinelearninggeek.com/sensitivity-analysis-in-python/ into Google OR Tools:

import pandas as pd
from ortools.linear_solver import pywraplp
from ortools.init import pywrapinit

solver = pywraplp.Solver.CreateSolver('GLOP')
A = solver.NumVar(0.0, solver.infinity(), "A")
B = solver.NumVar(0.0, solver.infinity(), "B")
solver.Add(4 * A + 10 * B <= 100, "c0")
solver.Add(2 * A + 1 * B <= 22, "c1")
solver.Add(3 * A + 3 * B <= 39, "c2")

solver.Maximize(60 * A + 50 * B )

status = solver.Solve()
if status == pywraplp.Solver.OPTIMAL:
    print('Solution:')
    print('Objective value =', solver.Objective().Value())
    print('A =', A.solution_value())
    print('B =', B.solution_value())
else:
    print('The problem does not have an optimal solution.')
    
activities = solver.ComputeConstraintActivities()
o = [{'Name':c.name(), 'shadow price':c.dual_value(), 'slack': c.ub() - activities[i]} for i, c in enumerate(solver.constraints())]
print(pd.DataFrame(o))

Output is

Solution:
Objective value = 740.0
A = 9.000000000000002
B = 3.9999999999999973
  Name  shadow price  slack
0   c0     -0.000000   24.0
1   c1     10.000000    0.0
2   c2     13.333333    0.0   

Shadow prices can be retrieved from constraint.dual_value() and slack by substracting the constraint activities from the upper bound of the constraint.