Given a function $g(x,y,z)$ we need to maximize it given constraints $a If the constraints were given as a function $f(x,y,z)$ the following equation could be used. $\nabla f(x,y,z) = \lambda \nabla g(x,y,z)$ How would I set up the initial equation given an interval constraint. Or how would I turn the interval constraint into a function constraint. EDIT:: Added $a
lagrange multiplier with interval constraint
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lagrange-multiplier
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0Hint: consider a function such as $(x-(a+b)/2)^2$ – 2012-11-10
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Maximize $g$ ignoring the constraint. If the solution fulfills the constraint, you're done. If not, there's no maximum, since it would have to lie on the boundary, but the boundary is excluded by the constraint.
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0Isn't that the same as taking the first/second partial derivative test ? Thus essentially not using Lagrange? What if the question specifically asks to use Lagrange ? – 2012-11-10
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0@Kassym: I don't see how it could make sense for the question to specifically ask to use a Lagrange multiplier. Even if the constraint were $a\le x\le b$, so you could find a maximum on the boundary, you'd still just have to substitute $a$ and $b$ for $x$ -- the only situation in which you'd need a Lagrange multiplier would be if the constraint were of the form $a\le f(x,y,z)\le b$; then, if the unconstrained maximization wouldn't yield a maximum satisfying the constraint, you could find the maximum on the boundary by setting $f(x,y,z)$ to $a$ and $b$ and then using a Lagrange multiplier. – 2012-11-10
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0@Kassym: Often people misunderstand problems and then present them in the misunderstood form, and there's no way to know what went wrong. You may want to quote the question verbatim to make sure that's not what's happened here. – 2012-11-10
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0http://dl.dropbox.com/u/24907/q3.png – 2012-11-10
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0@Kassym: Your question has little to do with the problem in that image, which does indeed require Lagrange multipliers. Next time please take more care in describing the problem, or provide a verbatim quote or link right away; that would have saved everyone a lot of time. – 2012-11-11