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Finding the maxima

Unconstrained optimization is finding the maxima or minima of a function that does not have any constraints or restrictions on the input variables.

Suppose you are launching a new product in your delicious cookie company and you want to maximize the revenue. The revenue can be modeled with this objective function where R is the revenue generated at price x.

R = -(x**2) + 3*x - 5

Solve this maximization problem using SciPys minimize_scalar() which has been loaded for you.

Este exercício faz parte do curso

Introduction to Optimization in Python

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Instruções do exercício

  • Define a new objective function that is the negation of the original objective function.
  • Maximize the negated function.
  • Print the optimal value to two decimal places.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Define the new objective function
def negated_function(x):
  ____

# Maximize the negated function
result = ____

# Print the result
print(f"The maximum is {____} in two decimals")
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