Kuhn-Tucker Theorem

The Kuhn-Tucker theorem is a theorem in nonlinear programming which states that if a regularity condition holds and f and the functions h_j are convex, then a solution x^((0)) which satisfies the conditions h_j for a vector of multipliers lambda is a global minimum. The Kuhn-Tucker theorem is a generalization of Lagrange multipliers. Farkas's lemma is key in proving this theorem.

See also

Farkas's Lemma, Lagrange Multiplier

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Kampas, F. J. "Tricks of the Trade: Using Reduce to Solve the Kuhn-Tucker Equations." Mathematica J. 9, 686-689, 2005.

Referenced on Wolfram|Alpha

Kuhn-Tucker Theorem

Cite this as:

Weisstein, Eric W. "Kuhn-Tucker Theorem." From MathWorld--A Wolfram Web Resource.

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