Exhaustive search method
You've applied the objective function and visualized the result; however, you could only eye-ball the optimal value by reviewing the plot. A more precise way of finding this value is with the exhaustive search method.
You're again working for a media company that publishes and prints magazines, but this time, you'll discover how to maximize profit rather than minimize cost. Recall that the profit and quantity units are in the thousands, so a q of 1 is 1000 magazines and a profit of 5 is $5000.
The same quantity array from the previous exercise has been provided for you, along with a profit() function to optimize.
numpy has been imported for you as np.
This exercise is part of the course
Introduction to Optimization in Python
Exercise instructions
- Calculate the profit for every quantity using the
profit()function provided, saving toprofits. - Find the maximum profit with the appropriate array method, saving to
max_profit. - Find the optimal quantity to maximize profit by saving the index of the maximum profit as
max_index, then using this to subsetquantity. - Print the results by completing the f-string, remembering to multiply the profit and quantity by
1000.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Calculate the profit for every quantity
profits = ____
# Find the maximum profit
max_profit = ____
# Find the optimal quantity
max_profit_ind = ____
optimal_quantity = ____
# Print the results
print(f"You need to print {____} magazines to make the maximum profit of ${____}.")