Adjusting MILP
The gown and tuxedo firm have adjusted some aspects of their business and need you to optimize for profit based on the new structure.
The profit formula was \(545g + 330t\), where \(g\) are the gowns, and \(t\) are the tuxedos. The constraints are the same: \(6g+4t<=40\), \(3g+t<=20\)
The firm wants to increase their tuxedo profit by 10%, and Mr. S can now only work 30 hours per week.
milp, LinearConstraint and Bounds have been loaded for you.
This exercise is part of the course
Introduction to Optimization in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Adjust the objective
result = milp([____, ____],
integrality=[1, 1],
bounds=Bounds([0, 0], [20, 12]),
constraints=LinearConstraint([[6, 4], [3, 1]], ub=[40, 20]))
print(result.message)
print(f'The optimal number of gowns produced is: {result.x[0]:.2f}')
print(f'The optimal number of tuxedos produced is: {result.x[1]:.2f}')
print(f'The firm made: ${-result.fun:.2f}')