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  2. Duality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Duality_(mathematics)

    A linear program may be specified by a system of real variables (the coordinates for a point in Euclidean space ), a system of linear constraints (specifying that the point lie in a halfspace; the intersection of these halfspaces is a convex polytope, the feasible region of the program), and a linear function (what to optimize).

  3. Dual linear program - Wikipedia

    en.wikipedia.org/wiki/Dual_linear_program

    The max-flow min-cut theorem is a special case of the strong duality theorem: flow-maximization is the primal LP, and cut-minimization is the dual LP. See Max-flow min-cut theorem#Linear program formulation. Other graph-related theorems can be proved using the strong duality theorem, in particular, Konig's theorem. [9]

  4. Dual system - Wikipedia

    en.wikipedia.org/wiki/Dual_system

    In mathematics, a dual system, dual pair or a duality over a field is a triple (,,) consisting of two vector spaces, and , over and a non-degenerate bilinear map:.. In mathematics, duality is the study of dual systems and is important in functional analysis.

  5. Total order - Wikipedia

    en.wikipedia.org/wiki/Total_order

    In mathematics, a total order or linear order is a partial order in which any two elements are comparable. That is, a total order is a binary relation ≤ {\displaystyle \leq } on some set X {\displaystyle X} , which satisfies the following for all a , b {\displaystyle a,b} and c {\displaystyle c} in X {\displaystyle X} :

  6. Screw theory - Wikipedia

    en.wikipedia.org/wiki/Screw_theory

    This is known as Chasles' theorem. The six parameters that define a screw motion are the four independent components of the Plücker vector that defines the screw axis, together with the rotation angle about and linear slide along this line, and form a pair of vectors called a screw.

  7. Linear independence - Wikipedia

    en.wikipedia.org/wiki/Linear_independence

    In the theory of vector spaces, a set of vectors is said to be linearly independent if there exists no nontrivial linear combination of the vectors that equals the zero vector. If such a linear combination exists, then the vectors are said to be linearly dependent. These concepts are central to the definition of dimension. [1]

  8. Pairing - Wikipedia

    en.wikipedia.org/wiki/Pairing

    A pairing can also be considered as an R-linear map: ⁡ (,), which matches the first definition by setting ():= (,). A pairing is called perfect if the above map Φ {\displaystyle \Phi } is an isomorphism of R -modules.

  9. Linear extension - Wikipedia

    en.wikipedia.org/wiki/Linear_extension

    The order dimension of a partial order is the minimum cardinality of a set of linear extensions whose intersection is the given partial order; equivalently, it is the minimum number of linear extensions needed to ensure that each critical pair of the partial order is reversed in at least one of the extensions.