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  2. Duality (optimization) - Wikipedia

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

    The Lagrangian dual program is the program of maximizing g: (). The optimal solution to the dual program is a lower bound for the optimal solution of the original (primal) program; this is the weak duality principle.

  3. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). [1] It is named after the mathematician Joseph-Louis ...

  4. Conjugate variables - Wikipedia

    en.wikipedia.org/wiki/Conjugate_variables

    The duality relations lead naturally to an uncertainty relation—in physics called the Heisenberg uncertainty principle—between them. In mathematical terms, conjugate variables are part of a symplectic basis , and the uncertainty relation corresponds to the symplectic form .

  5. Lagrangian relaxation - Wikipedia

    en.wikipedia.org/wiki/Lagrangian_relaxation

    A Lagrangian relaxation algorithm thus proceeds to explore the range of feasible values while seeking to minimize the result returned by the inner problem. Each value returned by P {\displaystyle P} is a candidate upper bound to the problem, the smallest of which is kept as the best upper bound.

  6. Action principles - Wikipedia

    en.wikipedia.org/wiki/Action_principles

    Action principles are "integral" approaches rather than the "differential" approach of Newtonian mechanics.[2]: 162 The core ideas are based on energy, paths, an energy function called the Lagrangian along paths, and selection of a path according to the "action", a continuous sum or integral of the Lagrangian along the path.

  7. Dual linear program - Wikipedia

    en.wikipedia.org/wiki/Dual_linear_program

    The strong duality theorem says that if one of the two problems has an optimal solution, so does the other one and that the bounds given by the weak duality theorem are tight, i.e.: max x c T x = min y b T y. The strong duality theorem is harder to prove; the proofs usually use the weak duality theorem as a sub-routine.

  8. Lagrangian - Wikipedia

    en.wikipedia.org/wiki/Lagrangian

    Lagrangian mechanics, a formulation of classical mechanics; Lagrangian (field theory), a formalism in classical field theory; Lagrangian point, a position in an orbital configuration of two large bodies; Lagrangian coordinates, a way of describing the motions of particles of a solid or fluid in continuum mechanics

  9. Karush–Kuhn–Tucker conditions - Wikipedia

    en.wikipedia.org/wiki/Karush–Kuhn–Tucker...

    Theorem — (sufficiency) If there exists a solution to the primal problem, a solution (,) to the dual problem, such that together they satisfy the KKT conditions, then the problem pair has strong duality, and , (,) is a solution pair to the primal and dual problems.