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  2. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    The Lagrange multiplier theorem states that at any local maximum (or minimum) of the function evaluated under the equality constraints, if constraint qualification applies (explained below), then the gradient of the function (at that point) can be expressed as a linear combination of the gradients of the constraints (at that point), with the ...

  3. Score test - Wikipedia

    en.wikipedia.org/wiki/Score_test

    Since function maximization subject to equality constraints is most conveniently done using a Lagrangean expression of the problem, the score test can be equivalently understood as a test of the magnitude of the Lagrange multipliers associated with the constraints where, again, if the constraints are non-binding at the maximum likelihood, the ...

  4. Duality (optimization) - Wikipedia

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

    The Lagrangian dual problem is obtained by forming the Lagrangian of a minimization problem by using nonnegative Lagrange multipliers to add the constraints to the objective function, and then solving for the primal variable values that minimize the original objective function. This solution gives the primal variables as functions of the ...

  5. Lagrangian mechanics - Wikipedia

    en.wikipedia.org/wiki/Lagrangian_mechanics

    Joseph-Louis Lagrange (1736–1813). In physics, Lagrangian mechanics is a formulation of classical mechanics founded on the stationary-action principle (also known as the principle of least action).

  6. Lagrangian relaxation - Wikipedia

    en.wikipedia.org/wiki/Lagrangian_relaxation

    The method penalizes violations of inequality constraints using a Lagrange multiplier, which imposes a cost on violations. These added costs are used instead of the strict inequality constraints in the optimization. In practice, this relaxed problem can often be solved more easily than the original problem.

  7. Principle of maximum entropy - Wikipedia

    en.wikipedia.org/wiki/Principle_of_maximum_entropy

    In the case with inequality moment constraints the Lagrange multipliers are determined from the solution of a convex optimization program. [11] The invariant measure function q(x) can be best understood by supposing that x is known to take values only in the bounded interval (a, b), and that no other information is given. Then the maximum ...

  8. Constrained optimization - Wikipedia

    en.wikipedia.org/wiki/Constrained_optimization

    If the constrained problem has only equality constraints, the method of Lagrange multipliers can be used to convert it into an unconstrained problem whose number of variables is the original number of variables plus the original number of equality constraints. Alternatively, if the constraints are all equality constraints and are all linear ...

  9. Adjoint state method - Wikipedia

    en.wikipedia.org/wiki/Adjoint_state_method

    where is a Lagrange multiplier or adjoint state variable and , is an inner product on . The method of Lagrange multipliers states that a solution to the problem has to be a stationary point of the lagrangian, namely