<jupyter_start><jupyter_text>---__Universidad Tecnológica Nacional, Buenos Aires__\__Ingeniería Industrial__\__Cátedra de Investigación Operativa__\__Autor: <NAME>__, <EMAIL>---<jupyter_code>import pulp

lp = pulp.LpProblem("ejercicio02", pulp.LpMaximize)

# Variables:
x = pulp.LpVariable('x', lowBound=0, cat='Continuous')
y = pulp.LpVariable('y', lowBound=0, cat='Continuous')

# Función objetivo:
lp += 5*x + 3*y, "Z"

# Restricciones
lp += 3*x + 2*y <= 2400
lp +=         y <=  800
lp += 2*x       <= 1200

# Resolvemos:
lp.solve()

# Imprimimos el status del problema:
print(pulp.LpStatus[lp.status])

# Imprimimos las variables en su valor óptimo:
for variable in lp.variables():
    print(f"{variable.name:s} = {variable.varValue:.2f}")

# Imprimimos el funcional óptimo:
print(pulp.value(lp.objective))<jupyter_output>Optimal
x = 600.00
y = 300.00
3900.0
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '241627', 'license': 'Apache-2.0', 'n_tokens_mistral': 375, 'n_tokens_neox': 340, 'n_words': 72, 'path': '07_programacion_matematica/casos_codigo/ejercicios/ejercicio02.ipynb', 'repo_name': 'juanntripaldi/pyOperativ', 'size': '893'}