Lagrangian multiplier question

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Homework Help Overview

The discussion revolves around finding the minimum and maximum values of the function f(x,y,z) = x^4 + y^4 + z^4, subject to the constraint x^2 + y^2 + z^2 = 1. Participants are exploring the application of Lagrange multipliers to solve this optimization problem.

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  • Mixed

Approaches and Questions Raised

  • Participants are attempting to apply the method of Lagrange multipliers, discussing the conditions derived from the Lagrangian. There are questions about the validity of certain points found and the implications of different cases when one or more variables are set to zero.

Discussion Status

Some participants have provided alternative perspectives on the application of the Lagrange multiplier method, suggesting that the original poster's findings may not align with the established conditions. There is an ongoing exploration of the implications of the derived equations and cases, with no explicit consensus reached on the correct approach.

Contextual Notes

There is a noted confusion regarding the setup of the Lagrangian and the conditions for optimization, with participants questioning assumptions about the relationships between the variables and the constraint. Some participants are also addressing the need for clarity on the conditions under which the Lagrange multiplier method applies.

autre
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So I have to find the min and max values of f(x,y,z) = x^4 + y^4 + z^ 4 given the constraint x^2 + y^2 + z^2 = 1. I've found the points (+-1/sqrt(3),1/sqrt(3) ,1/sqrt(3)), (+-1/sqrt(3),-1/sqrt(3) ,1/sqrt(3)) ... etc all of which have the f-value of 1/3 when x =/= 0 & y =/= 0 & z =/= 0 (this will probably turn out to be the min?)

My issue is the case when one value is zero and the other two are nonzero. I have 4x^3 = 2Lx (I'm using L for lambda here), then 2x^3 - Lx = 0, x(2x^2 - L) = 0...L = +-1/sqrt(2). From there, I have 2y^2 = L = 1/sqrt(2), y^2 = 1/2sqrt(2), and I'm not sure where to go from there for this case.
 
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autre said:
So I have to find the min and max values of f(x,y,z) = x^4 + y^4 + z^ 4 given the constraint x^2 + y^2 + z^2 = 1. I've found the points (+-1/sqrt(3),1/sqrt(3) ,1/sqrt(3)), (+-1/sqrt(3),-1/sqrt(3) ,1/sqrt(3)) ... etc all of which have the f-value of 1/3 when x =/= 0 & y =/= 0 & z =/= 0 (this will probably turn out to be the min?)

My issue is the case when one value is zero and the other two are nonzero. I have 4x^3 = 2Lx (I'm using L for lambda here), then 2x^3 - Lx = 0, x(2x^2 - L) = 0...L = +-1/sqrt(2). From there, I have 2y^2 = L = 1/sqrt(2), y^2 = 1/2sqrt(2), and I'm not sure where to go from there for this case.

I don't know how you found those points; they do not follow from the Lagrange conditions. For Lagrangian L = x^4 + y^4 + z^4 + u*(x^2 + y^2 + z^2 -1) [using u as the Lagrange multiplier and L as the Lagrangian] the conditions dL/dx = dL/dy = dL/dz = 0 give 2x - 2ux = 0, 2y - 2uy = 0, 2z - 2uz = 0. Thus, when x,y,z =/= 0 we have u = -1, and we have NO other conditions except g = 0. Although the Lagrange multiplier rule does hold at a max or min in this case (because the constraint qualification always holds), it gives no information. Instead, you can look at x1 = x^2, x2 = y^2, x3 = z^2 to get the problem max/min x1^2 + x2^2 + x3^2, subject to x1 + x2 + x3 = 1 and x1, x2, x3 >= 0. Using the Karush-Kuhn-Tucker conditions we find that x1 = x2 = x3 = 1/2 is the min, and that there are three maxima: (x1 = 0, x2 = x3 = 1/2) and permutations of this. Of course, now you can take square roots to get x, y and z.

RGV
 
the conditions dL/dx = dL/dy = dL/dz = 0 give 2x - 2ux = 0, 2y - 2uy = 0, 2z - 2uz = 0.

Isn't <4x^3, 4y^3, 4z^3> = u<2x, 2y, 2z>?
 
autre said:
Isn't <4x^3, 4y^3, 4z^3> = u<2x, 2y, 2z>?

Of course. Sorry: I really screwed that one up (I mistakenly wrote the Lagrangian for the problem of max/min x^2 + y^2 + z^2, subject to x^2 + y^2 + z^2 = 1, and of course I got no solution!). For Lagrangian L = x^4 + y^4 + z^4 + u*(x^2 + y^2 + z^2 - 1) the actual equations are 4x^3 + 2ux = 0, etc, so the solution is either: Case(1) x = 1, y = z = 0, u = -2 (and permutations thereof, or a sign change on x); Case(2) x = y = 1/sqrt(2), z = 0, u = -1 (and permutations, or sign changes on each x,y,z variable separately); Case(3) x = y = z = 1/sqrt(3) , u = -2/3 (or sign changes on each x,y,z variable separately). We have f(Case1) > f(Case2) > f(case(3). Second order tests show that Case(1) is a strict local max, Case(3) is a strict local min and Case(2) is neither. (Here, we look at the projection of the Hessian of the *Lagrangian* on the tangent subspace of the constraint and test for positive or negative definiteness therein.)

RGV
 

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