KKT

Author

Affiliation

Enrico Bertolazzi

University of Trento, Department of Industrial Engineering

The Karush-Kuhn-Tucker (KKT) conditions are a set of criteria used to determine whether a solution to a constrained optimization problem is optimal. They extend the method of Lagrange multipliers to handle not only equality constraints but also inequality constraints.

Learning objectives

After this part, you should be able to formulate a constrained minimization problem, distinguish necessary from sufficient optimality conditions, and apply the KKT conditions while checking an appropriate constraint qualification.

[1]

Dimitri P. Bertsekas. 2016. Nonlinear programming (3rd ed.). Athena Scientific.

[2]

Roger Fletcher. 2000. Practical methods of optimization (2nd ed.). John Wiley & Sons.

[3]

Jorge Nocedal and Stephen J. Wright. 2006. Numerical optimization (2nd ed.). Springer Science & Business Media. https://doi.org/10.1007/978-0-387-40065-5