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Facet Complexity
An ''n''-dimensional polyhedron is a geometric object that generalizes the 3-dimensional polyhedron to an ''n''-dimensional space. It is defined as a set of points in real affine (or Euclidean) space of any dimension ''n'', that has flat sides. It may alternatively be defined as the intersection of finitely many half-spaces. Unlike a 3-dimensional polyhedron, it may be bounded or unbounded. In this terminology, a bounded polyhedron is called a polytope... Analytically, a convex polyhedron is expressed as the solution set for a system of linear inequalities, ''ai''T''x'' ≤ ''bi'', where ''ai'' are vectors in R''n'' and ''bi'' are scalars. This definition of polyhedra is particularly important as it provides a geometric perspective for problems in linear programming. Examples Many traditional polyhedral forms are n-dimensional polyhedra. Other examples include: * A half-space is a polyhedron defined by a single linear inequality, ''a1''T''x'' ≤ ''b1''. * A hyperplane is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Polyhedron
In geometry, a polyhedron (: polyhedra or polyhedrons; ) is a three-dimensional figure with flat polygonal Face (geometry), faces, straight Edge (geometry), edges and sharp corners or Vertex (geometry), vertices. The term "polyhedron" may refer either to a solid figure or to its boundary surface (mathematics), surface. The terms solid polyhedron and polyhedral surface are commonly used to distinguish the two concepts. Also, the term ''polyhedron'' is often used to refer implicitly to the whole structure (mathematics), structure formed by a solid polyhedron, its polyhedral surface, its faces, its edges, and its vertices. There are many definitions of polyhedron. Nevertheless, the polyhedron is typically understood as a generalization of a two-dimensional polygon and a three-dimensional specialization of a polytope, a more general concept in any number of dimensions. Polyhedra have several general characteristics that include the number of faces, topological classification by Eule ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Boundary (topology)
In topology and mathematics in general, the boundary of a subset of a topological space is the set of points in the Closure (topology), closure of not belonging to the Interior (topology), interior of . An element of the boundary of is called a boundary point of . The term boundary operation refers to finding or taking the boundary of a set. Notations used for boundary of a set include \operatorname(S), \operatorname(S), and \partial S. Some authors (for example Willard, in ''General Topology'') use the term frontier instead of boundary in an attempt to avoid confusion with a Manifold#Manifold with boundary, different definition used in algebraic topology and the theory of manifolds. Despite widespread acceptance of the meaning of the terms boundary and frontier, they have sometimes been used to refer to other sets. For example, ''Metric Spaces'' by E. T. Copson uses the term boundary to refer to Felix Hausdorff, Hausdorff's border, which is defined as the intersection ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithmic Problems On Convex Sets
Many problems in mathematical programming can be formulated as problems on convex sets or convex bodies. Six kinds of problems are particularly important: optimization, violation, validity, separation, membership and emptiness. Each of these problems has a strong (exact) variant, and a weak (approximate) variant. In all problem descriptions, ''K'' denotes a compact and convex set in R''n''. Strong variants The strong variants of the problems are: * Strong optimization problem (SOPT): given a vector ''c'' in R''n'', find a vector ''y'' in ''K'' such that ''c''T''y'' ≥ ''c''T''x'' for all ''x'' in ''K'', or assert that ''K'' is empty. * Strong violation problem (SVIOL): given a vector ''c'' in R''n'' and a number ''t'', decide whether ''c''T''x'' ≤ ''t'' for all ''x'' in ''K'', or find ''y'' in ''K'' such that ''c''T''y'' > ''t''. * Strong validity problem (SVAL): given a vector ''c'' in R''n'' and a number ''t'', decide whether ''c''T''x'' ≤ ''t'' for all ''x'' in ''K''. * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Simultaneous Diophantine Approximation
In number theory, the study of Diophantine approximation deals with the approximation of real numbers by rational numbers. It is named after Diophantus of Alexandria. The first problem was to know how well a real number can be approximated by rational numbers. For this problem, a rational number ''p''/''q'' is a "good" approximation of a real number ''α'' if the absolute value of the difference between ''p''/''q'' and ''α'' may not decrease if ''p''/''q'' is replaced by another rational number with a smaller denominator. This problem was solved during the 18th century by means of simple continued fractions. Knowing the "best" approximations of a given number, the main problem of the field is to find sharp upper and lower bounds of the above difference, expressed as a function of the denominator. It appears that these bounds depend on the nature of the real numbers to be approximated: the lower bound for the approximation of a rational number by another rational number is lar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Carathéodory's Theorem (convex Hull)
Carathéodory's theorem is a theorem in convex geometry. It states that if a point x lies in the convex hull \mathrm(P) of a set P\subset \R^d, then x lies in some ''d''-dimensional simplex with vertices in P. Equivalently, x can be written as the convex combination of d+1 or fewer points in P. Additionally, x can be written as the convex combination of at most d+1 ''extremal'' points in P, as non-extremal points can be removed from P without changing the membership of ''x'' in the convex hull. An equivalent theorem for conical combinations states that if a point x lies in the conical hull \mathrm(P) of a set P\subset \R^d, then x can be written as the conical combination of at most d points in P. Two other theorems of Helly and Radon are closely related to Carathéodory's theorem: the latter theorem can be used to prove the former theorems and vice versa. The result is named for Constantin Carathéodory, who proved the theorem in 1911 for the case when P is Compact space, co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recession Cone
In mathematics, especially convex analysis, the recession cone of a set A is a cone containing all vectors such that A ''recedes'' in that direction. That is, the set extends outward in all the directions given by the recession cone. Mathematical definition Given a nonempty set A \subset X for some vector space X, then the recession cone \operatorname(A) is given by :\operatorname(A) = \. If A is additionally a convex set then the recession cone can equivalently be defined by :\operatorname(A) = \. If A is a nonempty closed convex set then the recession cone can equivalently be defined as :\operatorname(A) = \bigcap_ t(A - a) for any choice of a \in A. Properties * If A is a nonempty set then 0 \in \operatorname(A). * If A is a nonempty convex set then \operatorname(A) is a convex cone. * If A is a nonempty closed convex subset of a finite-dimensional Hausdorff space (e.g. \mathbb^d), then \operatorname(A) = \ if and only if A is bounded. * If A is a nonempty set then A + \ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Conic Hull
Given a finite number of vectors x_1, x_2, \dots, x_n in a real vector space, a conical combination, conical sum, or weighted sum''Convex Analysis and Minimization Algorithms'' by Jean-Baptiste Hiriart-Urruty, Claude Lemaréchal, 1993, pp. 101, 102/ref>''Mathematical Programming'', by Melvyn W. Jeter (1986) p. 68/ref> of these vectors is a vector of the form : \alpha_1x_1+\alpha_2x_2+\cdots+\alpha_nx_n where \alpha_i are non-negative real numbers. The name derives from the fact that the set of all conical sum of vectors defines a cone (possibly in a lower-dimensional subspace). Conical hull The set of all conical combinations for a given set ''S'' is called the conical hull of ''S'' and denoted ''cone''(''S'') or ''coni''(''S''). That is, :\operatorname (S)=\left\. By taking ''k'' = 0, it follows the zero vector (origin) belongs to all conical hulls (since the summation becomes an empty sum). The conical hull of a set ''S'' is a convex set. In fact, it is the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Identity Matrix
In linear algebra, the identity matrix of size n is the n\times n square matrix with ones on the main diagonal and zeros elsewhere. It has unique properties, for example when the identity matrix represents a geometric transformation, the object remains unchanged by the transformation. In other contexts, it is analogous to multiplying by the number 1. Terminology and notation The identity matrix is often denoted by I_n, or simply by I if the size is immaterial or can be trivially determined by the context. I_1 = \begin 1 \end ,\ I_2 = \begin 1 & 0 \\ 0 & 1 \end ,\ I_3 = \begin 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end ,\ \dots ,\ I_n = \begin 1 & 0 & 0 & \cdots & 0 \\ 0 & 1 & 0 & \cdots & 0 \\ 0 & 0 & 1 & \cdots & 0 \\ \vdots & \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & 0 & \cdots & 1 \end. The term unit matrix has also been widely used, but the term ''identity matrix'' is now standard. The term ''unit matrix'' is ambiguous, because it is also used for a matrix of on ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Affine Hull
In mathematics, the affine hull or affine span of a set ''S'' in Euclidean space R''n'' is the smallest affine set containing ''S'', or equivalently, the intersection of all affine sets containing ''S''. Here, an ''affine set'' may be defined as the translation of a vector subspace. The affine hull of ''S'' is what \operatorname S would be if the origin was moved to ''S''. The affine hull aff(''S'') of ''S'' is the set of all affine combinations of elements of ''S'', that is, :\operatorname (S)=\left\. Examples *The affine hull of the empty set is the empty set. *The affine hull of a singleton (a set made of one single element) is the singleton itself. *The affine hull of a set of two different points is the line through them. *The affine hull of a set of three points not on one line is the plane going through them. *The affine hull of a set of four points not in a plane in R''3'' is the entire space R''3''. Properties For any subsets S, T \subseteq X * \operatorname(\o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Basic Feasible Solution
In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables. Geometrically, each BFS corresponds to a vertex of the N-dimensional polyhedron, polyhedron of feasible solutions. If there exists an optimal solution, then there exists an optimal BFS. Hence, to find an optimal solution, it is sufficient to consider the BFS-s. This fact is used by the simplex algorithm, which essentially travels from one BFS to another until an optimal solution is found. Definitions Preliminaries: equational form with linearly-independent rows For the definitions below, we first present the linear program in the so-called ''equational form'': :maximize \mathbf \mathbf :subject to A\mathbf = \mathbf and \mathbf \ge 0 where: * \mathbf and \mathbf are vectors of size ''n'' (the number of variables); * \mathbf is a vector of size ''m'' (the number of constraints); * A is an ''m''-by-''n'' matrix; * \mathbf \ge 0 means that all variables ar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convex Hull
In geometry, the convex hull, convex envelope or convex closure of a shape is the smallest convex set that contains it. The convex hull may be defined either as the intersection of all convex sets containing a given subset of a Euclidean space, or equivalently as the set of all convex combinations of points in the subset. For a Bounded set, bounded subset of the plane, the convex hull may be visualized as the shape enclosed by a rubber band stretched around the subset. Convex hulls of open sets are open, and convex hulls of compact sets are compact. Every compact convex set is the convex hull of its extreme points. The convex hull operator is an example of a closure operator, and every antimatroid can be represented by applying this closure operator to finite sets of points. The algorithmic problems of finding the convex hull of a finite set of points in the plane or other low-dimensional Euclidean spaces, and its projective duality, dual problem of intersecting Half-space (geome ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Real Number
In mathematics, a real number is a number that can be used to measure a continuous one- dimensional quantity such as a duration or temperature. Here, ''continuous'' means that pairs of values can have arbitrarily small differences. Every real number can be almost uniquely represented by an infinite decimal expansion. The real numbers are fundamental in calculus (and in many other branches of mathematics), in particular by their role in the classical definitions of limits, continuity and derivatives. The set of real numbers, sometimes called "the reals", is traditionally denoted by a bold , often using blackboard bold, . The adjective ''real'', used in the 17th century by René Descartes, distinguishes real numbers from imaginary numbers such as the square roots of . The real numbers include the rational numbers, such as the integer and the fraction . The rest of the real numbers are called irrational numbers. Some irrational numbers (as well as all the rationals) a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
