Nonlinear constrained biscuits
That was some excellent baking!
Now can you solve the same problem again using NonlinearConstraint?
Recall the constraint for the bakeries is they need to fulfill a minimum of 140 pre-orders and each factory can make 100 biscuits daily.
minimize, Bounds, and NonlinearConstraint have been loaded for you as well as the revenue function R, cost function C, and profit function profit.
This exercise is part of the course
Introduction to Optimization in Python
Exercise instructions
- Define the constraints using the
lambdafunctionq, setting the lower and upper bounds. - Perform optimization by adding the optimization function, bounds, and constraints to
miminize().
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Redefine the problem with NonlinearConstraint
constraints = NonlinearConstraint(lambda q: ____, ____, ___)
# Perform optimization
result = minimize(lambda q: ____,
[50, 50],
bounds=____,
constraints=____)
print(result.message)
print(f'The optimal number of biscuits to bake in bakery A is: {result.x[0]:.2f}')
print(f'The optimal number of biscuits to bake in bakery B is: {result.x[1]:.2f}')
print(f'The bakery company made: ${-result.fun:.2f}')