Linear programming: How to find extreme points and extreme directions?

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The discussion centers on understanding extreme points and extreme directions in convex sets within linear programming. The original poster seeks guidance on how to find these points, noting that their textbook lacks examples. Additionally, they express confusion about the concept of slack variables, which are used to convert constraint inequalities into equations. A response clarifies that each constraint inequality typically corresponds to one slack variable and encourages continued reading for more examples. The conversation highlights the need for practical examples to better grasp these concepts in linear programming.
Arian.D
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Hi guys

I'm reading a book about linear programming and network flows. In chapter 2 when it talks about convex sets and their analysis it talks about extreme points and extreme directions of a convex set. I understand the definitions of extreme points and extreme directions, but I don't know how I should find them. Unfortunately the book doesn't show how to find them with examples. :( I also don't know what a 'slack variable' is. I guess it must've been defined somewhere but I missed it :/

Any helps would be appreciated.
 
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C'mon.. it's really an easy question. No one here has ever passed a course in linear programming? really?
 
Arian.D said:
Hi guys

I'm reading a book about linear programming and network flows. In chapter 2 when it talks about convex sets and their analysis it talks about extreme points and extreme directions of a convex set. I understand the definitions of extreme points and extreme directions, but I don't know how I should find them. Unfortunately the book doesn't show how to find them with examples.
It might be that the author is merely setting the stage by defining some terms before looking at some examples.
Arian.D said:
:( I also don't know what a 'slack variable' is. I guess it must've been defined somewhere but I missed it :/
Slack variables are used to turn constraint inequalities into equations. For example, if you have a constraint inequality 2x + 3y ≤ 10, you can rewrite this as 2x + 3y + a = 10, where a is a slack variable such that a ≥ 0.

Generally you'll have one slack variable for each constraint inequality.

If you keep reading, you'll probably run into some examples.
Arian.D said:
Any helps would be appreciated.
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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