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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.
As you would have noticed, this course doesn't explore modeling optimization problems as a linear program much. That is a separate topic and deserves an entire course on it.
A background in basic linear algebra is needed to understand the proofs. In case you face trouble with any of the lectures or assignments, feel free to reach out to me. I am always eager to help students. You can also schedule office hours from my website once a week (first come, first served) to clear your doubts.
Everything You Need to Know About Linear Programming basics
This course is a comprehensive and well-structured introduction to Linear Programming basics. The instructor, Krunal Patel, is a leading expert in the field with a wealth of experience in Teaching & Academics to share.
The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.
The course is divided into sections, each of which covers a different aspect related to Math. Each module contains a series of video lectures, readings, and hands-on exercises.
The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.
One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.
Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.
Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.
Overall, I highly recommend this course to anyone who is interested in learning Linear Programming basics. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.
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