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

lp01 = pulp.LpProblem("problema producción", pulp.LpMaximize)

# Variables:
x = pulp.LpVariable('x', lowBound=45, cat='Continuous')
y = pulp.LpVariable('y', lowBound=5, cat='Continuous')

# Función objetivo:
lp01 += (x - 45)  + (y - 5), "Z"

# Restricciones:
lp01 +=  50*x + 24*y <= 2400
lp01 +=  30*x + 33*y <= 2100

lp01.solve()
pulp.LpStatus[lp01.status]
print(pulp.LpStatus[lp01.status])

for variable in lp01.variables():
    print("%s = %.2f" % (variable.name, variable.varValue))
print(pulp.value(lp01.objective))<jupyter_output>Optimal
x = 45.00
y = 6.25
1.25
{'fraction_non_alphanumeric': 0.16457286432160803, 'fraction_numerical': 0.06407035175879397, 'mean_word_length': 5.376, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 6, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '430017', 'license': 'Apache-2.0', 'n_tokens_mistral': 365, 'n_tokens_neox': 325, 'n_words': 63, 'path': '07_programacion_matematica/casos_codigo/ejercicios/problema_produccion.ipynb', 'repo_name': 'juanntripaldi/pyOperativ', 'size': '826'}