The Fritz John conditions (abbr. FJ conditions), in mathematics, are a necessary condition for a solution in nonlinear programming to be optimal. 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:
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| - Fritz-John-Bedingungen (de)
- Fritz John conditions (en)
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| - Die Fritz-John-Bedingungen (abgekürzt FJ-Bedingungen) sind in der Mathematik ein notwendiges Optimalitätskriterium erster Ordnung in der nichtlinearen Optimierung. Sie sind eine Verallgemeinerung der Karush-Kuhn-Tucker-Bedingungen und kommen im Gegensatz zu diesen ohne Regularitätsbedingungen aus. Benannt sind sie nach dem US-amerikanischen Mathematiker deutscher Abstammung, Fritz John. (de)
- The Fritz John conditions (abbr. FJ conditions), in mathematics, are a necessary condition for a solution in nonlinear programming to be optimal. 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: (en)
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| - Die Fritz-John-Bedingungen (abgekürzt FJ-Bedingungen) sind in der Mathematik ein notwendiges Optimalitätskriterium erster Ordnung in der nichtlinearen Optimierung. Sie sind eine Verallgemeinerung der Karush-Kuhn-Tucker-Bedingungen und kommen im Gegensatz zu diesen ohne Regularitätsbedingungen aus. Benannt sind sie nach dem US-amerikanischen Mathematiker deutscher Abstammung, Fritz John. (de)
- The Fritz John conditions (abbr. FJ conditions), in mathematics, are a necessary condition for a solution in nonlinear programming to be optimal. 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 (MFCQ). In other words, the Fritz John condition is equivalent to the optimality condition KKT or not-MFCQ. (en)
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