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ENCN205-25S2 - Applied Data Analysis for Civil and Natural Systems

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Which of the following descriptions in terms of the Lagrange multiplier and KKT conditions are correct?

KKT condition method is solved by setting gradient of the Lagrange function as 0, then combined with the constraints.

Lagrange multiplier method is used to solve optimiztion problems with inequality constraints

Lagrange multiplier method is solved by setting gradient of the Lagrange function as 0, then directly combined with equantions such as μ×constraint=0.

Lagrange multiplier method is solved by setting gradient of the Lagrange function as 0, then directly combined with the constraints, no µ or λ terms should be involved.

KKT conditions method is used to solve optimiztion problems with equality constraints

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Lagrange multiplier method is used to solve optimiztion problems with equality constraints

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KKT method is solved by setting gradient of the Lagrange function as 0, then combined with equantions such as μ×constraint=0.

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KKT condition method is used to solve optimiztion problems with inequality constraints

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Both KKT condition and Lagrange multiplier method need to form a Lagrange function and take gradient of the Lagrange function.

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