Diskussion:Nonlinear Opt.: KKT- theorem 4

Your wiki arcticle for the KKT theorem is right.

You described the theory really precisely.

In your first KKT condition, there is a lambda missing (Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \frac{\partial L}{\partial x_{i}}= \frac{\partial f}{\partial x_{i}}- \sum_{i=1}^{m}\lambda_{i}* \frac{\partial g_{i}}{\partial x_{i}}\leq 0 )

Your explanation for the difference between maximization and minimization with the graph is really good and easy to understand. Also the other KKT conditions are easy to understand in your article.

Your example is also well choosen because it is multidimensional. But in your Lagrange functions are brackets missing: Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): L (x_1,x_2,\lambda) = x{_1}^2 + x{_2}^2 + x_2 - 1 - \lambda (x{_1}^2 + x{_2}^2 - 1)

In your secend step you may add some space between both equations.

The steps until the solution are described precisely.

Also your further informations is useful but maybe you could explain it within your example.

All in all a quite good wiki arcticle.