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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.

This exercise is part of the course

Supply Chain Analytics in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample 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]))
Edit and Run Code