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Handling multiple elements

The farmer wants to replicate the previous optimization function to detail with more complicated meals for other animals on the farm.

The previous code has been provided. Can you adjust the previous code to make it better at handling multiple variables?

pulp has been imported for you.

Este exercício faz parte do curso

Introduction to Optimization in Python

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Instruções do exercício

  • Adjust the variable definition to use LpVariable.dicts(), saving them as variables with the name "Food".
  • Adjust the objective function to use lpSum().

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

model = LpProblem("MinCost", LpMinimize) 

# Adjust the variable definition
C = LpVariable("C", lowBound=0)
S = LpVariable("S", lowBound=0) 

# Adjust the objective function
cost = {'C': 0.11, 'S': 0.28}
model += 0.28*S + 0.11*C

model += 40*variables['S'] + 10*variables['C'] >= 17*(variables['C']+variables['S']), "M_protein"
model += variables['S'] + 2.5*variables['C'] >= 2*(variables['C']+variables['S']), "M_fat"
model += variables['C'] + variables['S'] >= 7, "M_weight"

model.solve()
print(f"Cost = {value(model.objective):.2f}")
print(f"Pounds of soybean = {variables['S'].varValue:.2f}, pounds of corn = {variables['C'].varValue:.2f}")
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