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The method of Lagrange multipliers

  1. Apr 25, 2012 #1
    1. The problem statement, all variables and given/known data
    The problem of minimizing f(x1, x2) = x1^3
    subject to
    (x1 + 1)^3 = (x2 − 2)^2 is known to have a unique global solution. Use the method of Lagrange
    multipliers to find it. You should deal with the issue of whether a constraint qualification holds.


    2. Relevant equations

    The problem of minimizing f(x) = 2x1^2+ x2^2+2x1*x2 -4x1-5x2+x3 subject to
    2x1+x2+x3=0 is known to have a solution. Use the method of Lagrange
    multipliers to find it. You should deal with the issue of whether a constraint qualification holds.

    3. The attempt at a solution
    I know for the queation be , the first step is to get the gradient of 2x1+x2+x3=0 then show is it nonzero everywhere, then use the Lagrange multiplier , but how about (x1 + 1)^3 = (x2 − 2)^2?
     
  2. jcsd
  3. Apr 26, 2012 #2

    vela

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    First off, it doesn't make sense to say you're calculating the gradient of an equation. You calculate the gradient of a function.

    You want to write the constraint in the form ##g(x_1,x_2) = c## where c is a constant. You then calculate ##\nabla g##.
     
  4. Apr 26, 2012 #3

    HallsofIvy

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    What, exactly, is the question? You first say "minimize [itex]f(x_1,x_2)= x_1^3[/itex]" but under "relevant equations" you say "minimize [itex]f(x)= 2x_1^2+ x_2^2+2x_1*x_2 -4x_1-5x_2+x_3[/itex]". Are these two separate problems? Also how are [itex]x_1[/itex], [itex]x_2[/itex], and [itex]x^3[/itex] connected with x? Did you mean [itex]f(x_1, x_2, x_3)[/itex]?
     
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