The diet problem revisited
You are reviewing the financials for a farmer who asked you to revisit the diet of his pigs and cut on the cost if possible. The current cost minimization diet is based on the vet's recommendation for at least 17% protein, 2% fat, 7lb food following specifications
| Food | Cost ($/lb) | Protein (%) | Fat (%) |
|---|---|---|---|
| corn | 0.11 | 10 | 2.5 |
| soybean | 0.28 | 40 | 1 |
You have the information that the 7 lb was a rounded figure and could decrease to 6.6 lb. You are asked to see how changing the weight or fat constraints one at a time affects the minimum cost. You will solve the original problem as is and examine the slack and shadow price.
pulp has been imported for you and model has been defined as well as the variables C and S for corn and soybean.
Questo esercizio fa parte del corso
Introduction to Optimization in Python
Istruzioni dell'esercizio
- Print the slack of the Weight constraint.
- Check if the shadow price of the Weight constraint is greater than 0.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
model.constraints['Weight'] = C + S >= 7
model.solve()
print(f"Status: {LpStatus[model.status]}\n")
# Print the slack of the weight constraint
print("The slack of the Weight constraint is {}",
____.constraints['Weight'].____)
# Check if the shadow price is greater than 0
if ____.constraints['Weight'].____ > 0:
print('Tightening the constraint will increase minimum cost')