Describing Polyhedra by Extreme Points
and Extreme Rays
John Mitchell
Let
, where
is an
matrix,
is an
-vector, and
is an
-vector.
Assume rank(
)=
and
.
We look at the extreme points and extreme rays of
.
Definition 1
A point
is an extreme point of
if there do not exist
points
and
in
and a scalar
(with
and
)
such that
.
Proposition 1
is an extreme point of
if and only if
is a
zero-dimensional face of
.
Definition 2
Let
.
Any
is a ray of
.
Note:
is a convex cone. A set
is a cone if
,
implies
.
A point
is a ray of
if and only if for any point
the set
.
Definition 3
A ray
of
is an extreme ray if there do not exist rays
and a scalar
(with
for any
and
)
such that
.
Proposition 2
A vector
is an extreme ray of
if and only if
is a one-dimensional face of
.
Theorem 1
If
is finite
then there is an optimal solution that is an extreme point.
Theorem 2
If
is unbounded
then
has an extreme ray
with
.
This theorem is the basis for decomposition algorithms for linear programming.
Note that if we drop the assumption about the rank of
, we get
the following proposition:
Proposition 3
If
and rank(
)=
then
has a face of dimension
and no proper face of lower dimension.
John E. Mitchell
2006-01-13