Solving the model case study exercise
Continue the case study of the Capacitated Plant Location model of a car manufacture. The PuLP model has been completed and solved for you. It is stored in the variable model.
The decision variables x and y respectively represent the production quantities of the different regions, and if a production plant is opened. Additionally, two python lists loc and size have also been created, containing the different locations, and the two types of plant capacities. Finally, the input data for the model has been printed to the console for reference.
This exercise is part of the course
Supply Chain Analytics in Python
Exercise instructions
- Print the values of how much is produced and shipped from one region to another.
- Next, print the status value of the different regional plants of low and high capacity.
- Finally, print the objective value.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Print the Production Quantities
o = [{'prod':'{} to {}'.format(i,j), 'quantity':x[(i,j)].____}
for i in ____ for j in ____]
print(pd.DataFrame(o))
# Print the Plant Values of the different regions
o = [{'lowCap':y[(i,size[0])].____, 'highCap':y[(i,size[1])].____}
for i in ____]
print(pd.DataFrame(o, index=loc))
# Print the Objective Value
print('Objective = ', ____)