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Fritz John conditions

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The Fritz John conditions (abbr. FJ conditions), in mathematics, are a necessary condition for a solution in nonlinear programming to be optimal.[1] They are used as lemma in the proof of the Karush–Kuhn–Tucker conditions, but they are relevant on their own.

We consider the following optimization problem:

where ƒ is the function to be minimized, the inequality constraints and the equality constraints, and where, respectively, , and are the indices sets of inactive, active and equality constraints and is an optimal solution of , then there exists a non-zero vector such that:

if the and are linearly independent or, more generally, when a constraint qualification holds.

Named after Fritz John, these conditions are equivalent to the Karush–Kuhn–Tucker conditions in the case . When , the condition is equivalent to the violation of Mangasarian–Fromovitz constraint qualification (MFCQ). In other words, the Fritz John condition is equivalent to the optimality condition KKT or not-MFCQ.[citation needed]

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