Quadratic programming: Difference between revisions

Revision as of 21:28, 4 May 2005

Revision as of 07:17, 20 June 2005

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(1) <math>A\mathbf{x} \le b</math> (inequality constraint)

(2) <math>C\mathbf{x} = d</math> (equality contraintconstraint)

If <math>E</math> is positive definite then <math>f(\mathbf{x})</math> is a [[convex]] [[function (mathematics)|function]] and constraints are [[linear]] functions. We have from optimization theory that for point <math>\mathbf{x}</math> to be an optimum point it is necessary and sufficient that <math>\mathbf{x}</math> is a [[Karush-Kuhn-Tucker]] (KKT) point.