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  2. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    The method of Lagrange multipliers can be extended to solve problems with multiple constraints using a similar argument. Consider a paraboloid subject to two line constraints that intersect at a single point. As the only feasible solution, this point is obviously a constrained extremum.

  3. Karush–Kuhn–Tucker conditions - Wikipedia

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

    Allowing inequality constraints, the KKT approach to nonlinear programming generalizes the method of Lagrange multipliers, which allows only equality constraints. Similar to the Lagrange approach, the constrained maximization (minimization) problem is rewritten as a Lagrange function whose optimal point is a global maximum or minimum over the ...

  4. 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 ...

  5. 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 ...

  6. Lagrange multipliers on Banach spaces - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multipliers_on...

    In the field of calculus of variations in mathematics, the method of Lagrange multipliers on Banach spaces can be used to solve certain infinite-dimensional constrained optimization problems. The method is a generalization of the classical method of Lagrange multipliers as used to find extrema of a function of finitely many variables.

  7. 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.

  8. Quadratic programming - Wikipedia

    en.wikipedia.org/wiki/Quadratic_programming

    Quadratic programming is particularly simple when Q is positive definite and there are only equality constraints; specifically, the solution process is linear. By using Lagrange multipliers and seeking the extremum of the Lagrangian, it may be readily shown that the solution to the equality constrained problem

  9. Constraint (computational chemistry) - Wikipedia

    en.wikipedia.org/wiki/Constraint_(computational...

    Resolving the constraints of a rigid water molecule using Lagrange multipliers: a) the unconstrained positions are obtained after a simulation time-step, b) the gradients of each constraint over each particle are computed and c) the Lagrange multipliers are computed for each gradient such that the constraints are satisfied.