Many traditional polyhedral forms are n-dimensional polyhedra. Other examples include:
A subset F of a polyhedron P is called a face of P if there is a halfspace H (defined by some inequality a1Tx ≤ b1) such that H contains P and F is the intersection of H and P.4: 9
Suppose P is a polyhedron defined by Ax ≤ b, where A has full column rank. Then, v is a vertex of P if and only if v is a basic feasible solution of the linear system Ax ≤ b.5: 10
The representation of a polyhedron by a set of linear inequalities is not unique. It is common to define a standard representation for each polyhedron P:6: 9
If P is a polytope (a bounded polyhedron), then it can be represented by its set of vertices V, as P is simply the convex hull of V: P = conv(V).
If P is a general (possibly unbounded) polyhedron, then it can be represented as: P = conv(V) + cone(E), where V is (as before) the set of vertices of P, and E is another finite set, and cone denotes the conic hull. The set cone(E) is also called the recession cone of P.7: 10
Carathéodory's theorem states that, if P is a d-dimensional polytope, then every point in P can be written as a convex combination of at most d+1 affinely-independent vertices of P. The theorem can be generalized: if P is any d-dimensional polyhedron, then every point in P can be written as a convex combination of points v1,...,vs, v1+e1,...,v1+et with s+t ≤ d+1, such that v1,...,vs are elements of minimal nonempty faces of P and e1,...,et are elements of the minimal nonzero faces of the recession cone of P.8: 10
When solving algorithmic problems on polyhedra, it is important to know whether a certain polyhedron can be represented by an encoding with a small number of bits. There are several measures to the representation complexity of a polyhedron P:9: 163
These two kinds of complexity are closely related:10: Lem.6.2.4
A polyhedron P is called well-described if we know n (the number of dimensions) and f (an upper bound on the facet complexity). This is equivalent to requiring that we know n and v (an upper bound on the vertex complexity).
In some cases, we know an upper bound on the facet complexity of a polyhedron P, but we do not know the specific inequalities that attain this upper bound. However, it can be proved that the encoding length in any standard representation of P is at most 35 n2 f.11: Lem.6.2.3
The complexity of representation of P implies upper and lower bounds on the volume of P:12: 165
Small representation complexity is useful for "rounding" approximate solutions to exact solutions. Specifically:13: 166
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Bruns, Winfried; Gubeladze, Joseph (2009), "Definition 1.1", Polytopes, Rings, and K-theory, Springer Monographs in Mathematics, Dordrecht: Springer, p. 5, CiteSeerX 10.1.1.693.2630, doi:10.1007/b105283, ISBN 978-0-387-76355-2, MR 2508056. 978-0-387-76355-2 ↩
Grötschel, Martin; Lovász, László; Schrijver, Alexander (1993), Geometric algorithms and combinatorial optimization, Algorithms and Combinatorics, vol. 2 (2nd ed.), Springer-Verlag, Berlin, doi:10.1007/978-3-642-78240-4, ISBN 978-3-642-78242-8, MR 1261419 978-3-642-78242-8 ↩