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

# Specifying the constraints

**1. Each box can only have one value.**

To ensure that each box has only one value, we can keep `row` and `col` constant and vary `values` from 1 to 9. The sum of the binary values should be equal to 1 since only one variable will be equal to 1 and others must be 0, like this:

(value = 1, row =1, col =1) + (value = 2, row =1, col =1) + (value = 3, row =1, col =1) + (value = 4, row =1, col =1) + (value = 5, row =1, col =1) + (value = 6, row =1, col =1) + (value = 7, row =1, col =1) +(value = 8, row =1, col =1) +(value = 9, row =1, col =1) == 1

We will need to perform this check for all different combinations of `row` and `col`.

Learn how to solve the Sudoku problem in linear programming given a set of constraints.


Problem: Solving Sudoku Using PuLP, Part II

Learn how to solve the Sudoku problem in linear programming given a set of constraints.