An example of a Pulp maximized optimization problem You make custom T-shirts with inspirational sayings on them. You just found out about a community flea market sale that is starting tomorrow. You have just 8 hours to prepare product for this sale. You start with a plain white T-shirt. This is your most popular color. But you can dye the white T-shirt blue, yellow, or red—but only one shirt at a time. Your current inventory is 50 white T-shirts and you have enough dye to make 12 red shirts, 10 yellow shirts, and 15 blue shirts. You take the various color shirts to the sale and then stencil on an inspirational saying—whatever the customer wants up to 35 characters.

Based on experience, you know that at a sale like this, you will be able to sell all 50 shirts. Use the data in the table below to determine how many shirts of each color you should bring to the sale to maximize your profits.

The problem was solved in Python using the PuLP module.