KKT conditions

E321097

KKT conditions are a set of necessary (and under certain conditions, sufficient) optimality conditions used in nonlinear programming to characterize solutions of constrained optimization problems.

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Predicate Object
instanceOf mathematical concept
nonlinear programming concept
optimality conditions
appliesTo constrained optimization problems
equality constrained optimization problems
inequality constrained optimization problems
nonlinear programming problems
are necessary conditions for optimality under regularity assumptions
sufficient conditions for optimality under convexity assumptions
areNecessaryFor local optima under suitable constraint qualifications
areSufficientFor global optima in convex optimization problems
assumes constraint qualifications such as Slater condition for necessity
category first-order optimality conditions
component complementary slackness condition
constraint qualification assumption
dual feasibility condition
primal feasibility condition
stationarity condition
field mathematical programming
operations research
optimization theory
fullName Karush–Kuhn–Tucker conditions
generalize Lagrange multiplier conditions
first-order necessary conditions for constrained optimization
historicalOrigin Karush–Kuhn–Tucker conditions
surface form: Karush 1939 master’s thesis

Kuhn and Tucker 1951 paper
imply nonnegativity of Lagrange multipliers for inequality constraints
product of multiplier and constraint function equals zero for each inequality constraint
zero gradient of Lagrangian with respect to primal variables at optimum
namedAfter Albert W. Tucker
Harold W. Kuhn
William Karush
relatedConcept Fritz John conditions
Lagrangian function
Slater’s condition
constraint qualification
dual problem in optimization
strong duality
relates primal variables and Lagrange multipliers
requires differentiability of constraint functions for standard form
differentiability of objective function for standard form
usedIn control theory
convex optimization
economics
engineering design optimization
machine learning
nonlinear optimization
support vector machines

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