extreme point

In mathematics, an extreme point of a convex set $S$ in a real or complex vector space is a point in $S$ that does not lie in any open line segment joining two points of $S.$ The extreme points of a line segment are called its '' endpoints''. In linear programming problems, an extreme point is also called '' vertex'' or ''corner point'' of $S.$

Definition

Throughout, it is assumed that $X$ is a real or complex vector space.

For any $p, x, y \in X,$ say that $p$ $x$ and $y$ if $x \neq y$ and there exists a $0 < t < 1$ such that $p = t x + (1-t) y.$

If $K$ is a subset of $X$ and $p \in K,$ then $p$ is called an of $K$ if it does not lie between any two points of $K.$ That is, if there does exist $x, y \in K$ and $0 < t < 1$ such that $x \neq y$ and $p = t x + (1-t) y.$ The set of all extreme points of $K$ is denoted by $\operatorname(K).$

Generalizations

If $S$ is a subset of a vector space then a linear sub-variety (that is, an affine subspace) $A$ of the vector space is called a if $A$ meets $S$ (that is, $A \cap S$ is not empty) and every open segment $I \subseteq S$ whose interior meets $A$ is necessarily a subset of $A.$ A 0-dimensional support variety is called an extreme point of $S.$

Characterizations

The of two elements $x$ and $y$ in a vector space is the vector $\tfrac(x+y).$

For any elements $x$ and $y$ in a vector space, the set $$, y= \ is called the or between $x$ and $y.$ The or between $x$ and $y$ is $(x, x) = \varnothing$ when $x = y$ while it is $(x, y) = \$ when $x \neq y.$ The points $x$ and $y$ are called the of these interval. An interval is said to be a or a if its endpoints are distinct. The is the midpoint of its endpoints.

The closed interval $$, y/math> is equal to the convex hull of $(x, y)$ if (and only if) $x \neq y.$ So if $K$ is convex and $x, y \in K,$ then $$, y\subseteq K.

If $K$ is a nonempty subset of $X$ and $F$ is a nonempty subset of $K,$ then $F$ is called a of $K$ if whenever a point $p \in F$ lies between two points of $K,$ then those two points necessarily belong to $F.$

Examples

If $a < b$ are two real numbers then $a$ and $b$ are extreme points of the interval , b However, the open interval $(a, b)$ has no extreme points.
Any open interval in $\R$ has no extreme points while any non-degenerate closed interval not equal to $\R$ does have extreme points (that is, the closed interval's endpoint(s)). More generally, any open subset of finite-dimensional Euclidean space $\R^n$ has no extreme points.

The extreme points of the closed unit disk in $\R^2$ is the unit circle.

The perimeter of any convex polygon in the plane is a face of that polygon.
The vertices of any convex polygon in the plane $\R^2$ are the extreme points of that polygon.

An injective linear map $F : X \to Y$ sends the extreme points of a convex set $C \subseteq X$ to the extreme points of the convex set $F(X).$ This is also true for injective affine maps.

Properties

The extreme points of a compact convex set form a Baire space (with the subspace topology) but this set may to be closed in $X.$

Theorems

Krein–Milman theorem

The Krein–Milman theorem is arguably one of the most well-known theorems about extreme points.

For Banach spaces

These theorems are for Banach spaces with the Radon–Nikodym property.

A theorem of Joram Lindenstrauss states that, in a Banach space with the Radon–Nikodym property, a nonempty closed and bounded set has an extreme point. (In infinite-dimensional spaces, the property of compactness is stronger than the joint properties of being closed and being bounded.)

Edgar’s theorem implies Lindenstrauss’s theorem.

Related notions

A closed convex subset of a topological vector space is called if every one of its (topological) boundary points is an extreme point. The unit ball of any Hilbert space is a strictly convex set.

''k''-extreme points

More generally, a point in a convex set $S$ is $k$-extreme if it lies in the interior of a $k$-dimensional convex set within $S,$ but not a $k + 1$-dimensional convex set within $S.$ Thus, an extreme point is also a $0$-extreme point. If $S$ is a polytope, then the $k$-extreme points are exactly the interior points of the $k$-dimensional faces of $S.$ More generally, for any convex set $S,$ the $k$-extreme points are partitioned into $k$-dimensional open faces.

The finite-dimensional Krein–Milman theorem, which is due to Minkowski, can be quickly proved using the concept of $k$-extreme points. If $S$ is closed, bounded, and $n$-dimensional, and if $p$ is a point in $S,$ then $p$ is $k$-extreme for some $k \leq n.$ The theorem asserts that $p$ is a convex combination of extreme points. If $k = 0$ then it is immediate. Otherwise $p$ lies on a line segment in $S$ which can be maximally extended (because $S$ is closed and bounded). If the endpoints of the segment are $q$ and $r,$ then their extreme rank must be less than that of $p,$ and the theorem follows by induction.

See also

* Extreme set
* Exposed point
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* Bang–bang control

Citations

Bibliography

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{{Topological vector spaces

Convex geometry
Convex hulls
Functional analysis
Mathematical analysis