Basic solution (linear programming)

In linear programming, a discipline within applied mathematics, a basic solution is any solution of a linear programming problem satisfying certain specified technical conditions.

For a polyhedron $P$ and a vector $𝐱^{*} \in ℝ^{n}$ , $𝐱^{*}$ is a basic solution if:

All the equality constraints defining $P$ are active at $𝐱^{*}$
Of all the constraints that are active at that vector, at least $n$ of them must be linearly independent. Note that this also means that at least $n$ constraints must be active at that vector.

A constraint is active for a particular solution $𝐱$ if it is satisfied at equality for that solution.

A basic solution that satisfies all the constraints defining $P$ (or, in other words, one that lies within $P$ ) is called a basic feasible solution.

References

↑ Bertsimas, Dimitris; Tsitsiklis, John N. (1997). Introduction to linear optimization. Belmont, Mass.: Athena Scientific. p. 50. ISBN 978-1-886529-19-9.

This applied mathematics–related article is a stub. You can help Wikipedia by adding missing information.

[1] Bertsimas, Dimitris; Tsitsiklis, John N. (1997). Introduction to linear optimization. Belmont, Mass.: Athena Scientific. p. 50. ISBN 978-1-886529-19-9.