Simulation testing capacitated model
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 you for reference.
Cet exercice fait partie du cours
Supply Chain Analytics in Python
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Define Objective
model += (lpSum([fix_cost.loc[i,s] * y[(i,s)] for s in size for i in loc])
+ lpSum([(var_cost.loc[i,j] + ____)*x[(i,j)]
for i in loc for j in loc]))