Trying out lpSum
In this exercise you are making two types (premium and budget) of ice cream, using heavy cream, whole milk, and sugar. One version is a premium version containing more cream than your budget version. You are looking to find the mixture of ingredients that minimizes the total costs of ingredients.
| Ingredient | $/cup |
|---|---|
| Cream | $1.5 |
| Milk | $0.125 |
| Sugar | $0.10 |
Two Python lists called prod_type and ingredient have been created for you, along with a dictionary var_dict containing the decision variables of the model. You can explore them in the console.
This is a part of the course
“Supply Chain Analytics in Python”
Exercise instructions
- Define the objective function using
lpSum()with list comprehension and the information in the table above. Iterate over the product types and multiply the dictionary variable by the correct ingredient cost.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Define Objective Function
model += lpSum([1.5 * var_dict[(i, 'cream')]
+ ____ * var_dict[(i, 'milk')]
+ ____ * var_dict[(i, ____)]
# Iterate over product types
for i in ____])