KKT Conditions (Karush-Kuhn-Tucker Conditions)

The Karush-Kuhn-Tucker (KKT) Conditions are a set of mathematical rules used to find the best solutions in optimization problems with constraints. They help determine the optimal point where a function reaches its maximum or minimum while satisfying certain conditions, such as limits or restrictions. Think of it like balancing a scale: the conditions ensure that the solution not only optimizes the objective but also respects the constraints. These conditions are fundamental in fields like economics, engineering, and machine learning for solving complex decision-making problems efficiently.