Corner Point Calculator

Corner Point Calculator

Identify the vertices of a feasible region for linear programming problems.

Last updated: 2026-05-24T22:58:31.624Z | By ForgeCalc Engineering

x
y
x
y

* Assumes x ≥ 0 and y ≥ 0

Corner Points (Vertices)
(0, 0)
(0, 10)
(7.5, 0)
(5, 5)

Enter numeric coefficients for constraints in the form ax + by ≤ c. Values must parse as numbers to participate in the computation.

What are Corner Points?

In linear programming, corner points (or vertices) are the points where the boundary lines of the feasible region intersect. The feasible region is the set of all possible points that satisfy a system of linear inequalities.

The Fundamental Theorem of Linear Programming states that if an optimal solution exists, it must occur at one of these corner points. This makes identifying them the most critical step in solving optimization problems.

How to Find Corner Points

Step-by-Step Method

  1. Graph each linear inequality as an equation (a line).
  2. Identify the intersection points of these lines with each other.
  3. Identify the intersection points of these lines with the x and y axes.
  4. Test each intersection point against all the original inequalities.
  5. Only the points that satisfy all inequalities are corner points of the feasible region.

Example Calculation

Constraints: x + y ≤ 10, 2x + y ≤ 15, x ≥ 0, y ≥ 0

Step 1: Intersections with axes (0,0), (10,0), (0,10), (7.5,0), (0,15)

Step 2: Intersection of lines x + y = 10 and 2x + y = 15. Subtracting gives x = 5, then y = 5. Point: (5,5)

Step 3: Test points (0,0) is valid. (7.5,0) is valid. (5,5) is valid. (0,10) is valid. (10,0) is invalid (2*10+0 > 15).

Final Answer: Corner points are (0,0), (7.5,0), (5,5), (0,10)

Frequently Asked Questions

Why are corner points important?

They are the only candidates for the maximum or minimum value of a linear objective function. This is known as the Corner Point Theorem.

What if the feasible region is unbounded?

If the region is unbounded, a maximum value might not exist, but a minimum value (if it exists) will still occur at a corner point.

Can there be multiple optimal solutions?

Yes. If the objective function line is parallel to one of the constraint lines, every point on that segment (including two corner points) is an optimal solution.

How many corner points can a region have?

A region defined by $n$ constraints can have at most $n(n-1)/2$ intersection points, though usually far fewer are actually corner points of the feasible region.

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