pulp.tar.gz

pulp

We make optimization decisions every day. To improve the performance of your applications, computers need to do the same. This course will help you optimize computing functions through the open-source Python library PuLP.

In this course, you’ll learn about linear programming, an optimization approach that maximizes or minimizes functions through defined algebra, and the PuLP library along with its various optimizers available via APIs. You’ll identify the variables and constraints of computing functions and define the optimization goals. You’ll then learn and practice common linear programming algorithms. Finally, you’ll be introduced to potential applications in the real world.

By the end of the course, you will be able to optimize computing functions using Python and PuLP.

Master Linear Programming in Python with PuLP

## Food and agriculture

Those who work in agriculture have the enormous responsibility to meet the food requirements of the population. Therefore, a natural constraint exists between the supply and demand of food. In agriculture, linear programming is employed to make smart decisions about the expenditure and distribution of resources.

- **Maximizing crop yields** Linear programming is used to maximize the yield of crops by taking into consideration different constraints, such as nutrient concentration, demand for the crop, and its profitability.

- **Food distribution** Linear programming is used to optimize the distribution of food to different regions. Multiple factors like the food’s shelf life, transportation cost, and demand for the product serve as the constraining variable for the optimization problem.

- **Diet plan** Linear programming is used by nutritionists to optimize the calorie intake for a healthy and balanced diet.

# Food and agriculture

Those who work in agriculture have the enormous responsibility to meet the food requirements of the population. Therefore, a natural constraint exists between the supply and demand of food. In agriculture, linear programming is employed to make smart decisions about the expenditure and distribution of resources.

- **Maximizing crop yields** Linear programming is used to maximize the yield of crops by taking into consideration different constraints, such as nutrient concentration, demand for the crop, and its profitability.

- **Food distribution** Linear programming is used to optimize the distribution of food to different regions. Multiple factors like the food’s shelf life, transportation cost, and demand for the product serve as the constraining variable for the optimization problem.

- **Diet plan** Linear programming is used by nutritionists to optimize the calorie intake for a healthy and balanced diet.

Summarizing the applications of linear programming in real life.

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Real-life Examples of Linear Programming in Python

Food and agriculture