# Linear Programming basics – (Free Course)

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## What you’ll learn

1. Describe what a linear program is.
2. Solve a linear program using graphical and simplex methods.
3. Compute the dual of the given linear program.
4. Use the primal and dual values to prove optimality or infeasibility of the given linear program..
5. Compute how the solution value changes under minor modification of the given linear program.

## This course includes:

• 3 hours on-demand video
• 5 articles
• Access on mobile and TV
• Certificate of completion

## Description

Linear programming is a widely used optimization tool in various applications (data science, engineering, transportation, supply chain, etc.). Linear programming also makes the basic foundation behind complex optimization tools like Mixed Integer Linear Programming (MILP) and Column generation. In this course, we will study the basic theoretical concepts related to linear programming.

The course is organized as follows. In the first section, we will introduce linear programming, and we will explore the convexity and types of optimalities. Then, in the second section, we will build up on the basics to learn ways to solve the linear program using the simplex method. We will then explore the concept of linear programming duality. We will also go through some of the hardest-to-understand concepts like strong duality, complementary slackness, and Farkas’ lemma. Furthermore, we try to understand these concepts in an easy-to-follow way. This allows one to obtain lower bounds on the minimization problem and provide proof of optimality or Infeasibility. In the last section, we will explore how to perform sensitivity analysis (the effects of changing parts of a linear program). At the end of each section, there are assignments to help you evaluate your knowledge.