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I am just beginning to read about the use of "Concave Programming" methods and use of the Karush-Kuhn-Tucker conditions to identify the maximum value of a non-linear objective function subject to inequality constraints.

The examples I have seen in the text I have at hand, all involve only linear constraints. Is this method equally applicable to situations where not only are there multiple constraints, but where one or more of those constraints are non-linear ?

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    Not a real question; vote to close.2010-10-24
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    There *is* a mathematical question in there: "Are the Karush-Kuhn-Tucker conditions applicable to situations where one or more of the constraints are non-linear?" The answer is yes. Any book on nonlinear optimization should have the details.2010-10-24
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    @Rahul: fair enough; perhaps what the question needs is a massive edit to remove the last four, irrelevant, paragraphs.2010-10-24
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    @Arturo: I agree. Dear @Michael Barkusky: You seem to have misunderstood the purpose of this site. It is designed specifically to answer questions about mathematics, and is not a general-purpose discussion forum. As such, the last four paragraphs of your post are out of place here, and your question may get a better reception if you edit them out.2010-10-24
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    I would just add to Rahul Narain's comment that not only can the KKT conditions be applied to problems with nonlinear constraints, part of the reason they were derived in the first place was to handle problems with nonlinear constraints.2010-10-25

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