Max min, Lagrange's multiplier question

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In summary, the conversation discusses using Lagrange's multiplier to solve for a constrained optimization problem involving a function S and a constraint G. The attempt at a solution involves setting up equations and using the gradient to solve for x1, x2, . . . , x2006 and lambda. It is suggested to complete the equation \nabla S= \lambda \cdot \nabla G to obtain 2007 linear equations for the variables.
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chy1013m1
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Homework Statement


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Homework Equations


possibly Lagrange's multiplier..

The Attempt at a Solution


treating S = f(x1, x2, ... , x2006) = x1 * 1^1/3 + x2 * 2^1/3 + ... + x2006 * 2006^1/3

and constrain G(x1, x2 ... x2006) = x1 ^ 3/2 + x2 ^ 3/2 + ... + x2006 ^ 3/2 - (2^1/2 / (2006^1/2 * 2007 ^ 1/2)) = 0

then solve G(x...) = 0
gradient(f) = lambda * gradient(G) , which isn't all that clear what to do next.. any hints ?
 
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It isn't clear what to do next? How about completing that equation:
[itex]\nabla S= \lambda \cdot \nabla G[/itex]? (S, not f)
What is [itex]\nabla S[/itex]? What is [itex]\nabla G[/itex]? That should give you 2007 linear equations for x1, x2, . . . , x2006 and [itex]\lambda[/itex]. Fortunately they are almost all separated and solving just a few should give you the general formula.
 

1. What is the concept of max min and Lagrange's multiplier?

Max min and Lagrange's multiplier are mathematical techniques used to optimize a function subject to certain constraints. Max min refers to finding the maximum or minimum value of a function, while Lagrange's multiplier is a method for finding the maximum or minimum value of a function subject to a constraint.

2. How do I solve a max min problem using Lagrange's multiplier?

To solve a max min problem using Lagrange's multiplier, you first need to set up the Lagrangian function by adding the constraint to the objective function with a Lagrange multiplier. Then, you take partial derivatives of the Lagrangian function with respect to each variable and set them equal to zero. Solving this system of equations will give you the optimal values for the variables.

3. What types of problems can be solved using max min and Lagrange's multiplier?

Max min and Lagrange's multiplier can be used to solve a variety of optimization problems, such as finding the minimum cost for a given production level or maximizing the profit for a given set of constraints. These techniques are commonly used in economics, engineering, and other fields that involve optimization.

4. Are there any limitations to using max min and Lagrange's multiplier?

One limitation of max min and Lagrange's multiplier is that they can only be used for differentiable functions. Additionally, the solutions obtained using these methods may not always be global optima, meaning there could be other, better solutions that are not found using these techniques.

5. Can I use technology to solve max min and Lagrange's multiplier problems?

Yes, there are various software programs and calculators that can assist in solving max min and Lagrange's multiplier problems. However, it is important to understand the underlying concepts and techniques in order to use these tools effectively.

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