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  2. Weak duality - Wikipedia

    en.wikipedia.org/wiki/Weak_duality

    In applied mathematics, weak duality is a concept in optimization which states that the duality gap is always greater than or equal to 0. This means that for any minimization problem, called the primal problem, the solution to the primal problem is always greater than or equal to the solution to the dual maximization problem.

  3. Perturbation function - Wikipedia

    en.wikipedia.org/wiki/Perturbation_function

    The duality gap is the difference of the right and left hand side of the inequality (,) (,),where is the convex conjugate in both variables. [3] [4]For any choice of perturbation function F weak duality holds.

  4. Duality (optimization) - Wikipedia

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

    The duality gap is zero if and only if strong duality holds. Otherwise the gap is strictly positive and weak duality holds. [5] In computational optimization, another "duality gap" is often reported, which is the difference in value between any dual solution and the value of a feasible but suboptimal iterate for the primal problem.

  5. Dual linear program - Wikipedia

    en.wikipedia.org/wiki/Dual_linear_program

    The weak duality theorem says that, for each feasible solution x of the primal and each feasible solution y of the dual: c T x ≤ b T y. In other words, the objective value in each feasible solution of the dual is an upper-bound on the objective value of the primal, and objective value in each feasible solution of the primal is a lower-bound ...

  6. Duality gap - Wikipedia

    en.wikipedia.org/wiki/Duality_gap

    This alternative "duality gap" quantifies the discrepancy between the value of a current feasible but suboptimal iterate for the primal problem and the value of the dual problem; the value of the dual problem is, under regularity conditions, equal to the value of the convex relaxation of the primal problem: The convex relaxation is the problem ...

  7. Wolfe duality - Wikipedia

    en.wikipedia.org/wiki/Wolfe_duality

    In mathematical optimization, Wolfe duality, named after Philip Wolfe, is type of dual problem in which the objective function and constraints are all differentiable functions. Using this concept a lower bound for a minimization problem can be found because of the weak duality principle.

  8. Equivalence of categories - Wikipedia

    en.wikipedia.org/wiki/Equivalence_of_categories

    A functor F : C → D yields an equivalence of categories if and only if it is simultaneously: . full, i.e. for any two objects c 1 and c 2 of C, the map Hom C (c 1,c 2) → Hom D (Fc 1,Fc 2) induced by F is surjective;

  9. Montonen–Olive duality - Wikipedia

    en.wikipedia.org/wiki/Montonen–Olive_duality

    Montonen–Olive duality or electric–magnetic duality is the oldest known example of strong–weak duality [note 1] or S-duality according to current terminology. [note 2] It generalizes the electro-magnetic symmetry of Maxwell's equations by stating that magnetic monopoles, which are usually viewed as emergent quasiparticles that are "composite" (i.e. they are solitons or topological ...