Solve Lagrange Multipliers Problem with x-4y=1 Constraint

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SUMMARY

The discussion focuses on solving the Lagrange Multipliers problem for the function \(f(x,y)=xy^{2}\) under the constraint \(x-4y=1\) and the additional bounds \(-1\leqslant x\leq 2\). The critical points identified are \((1,0)\), \(\left(\frac{1}{3},-\frac{1}{6}\right)\), \(\left(-1,-\frac{1}{2}\right)\), and \(\left(2,\frac{1}{4}\right)\). Evaluating the objective function at these points allows for determining the minimum and maximum values of the function within the specified constraints.

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  • Understanding of Lagrange Multipliers
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  • Knowledge of evaluating functions under constraints
  • Basic algebra for solving equations
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Students and professionals in mathematics, particularly those studying optimization techniques, as well as anyone interested in applying Lagrange Multipliers to solve constrained optimization problems.

Yankel
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Hello all

I have this problem:

Use Lagrange Multipliers to find the min and max of:

\[f(x,y)=xy^{2}\]

under the constraint:

\[x-4y=1\]

\[-1\leqslant x\leq 2\]

My problem is: I know how to solve if

\[-1\leqslant x\leq 2\]

wasn't given. I calculate the Lagrangian function, find it's derivatives by x,y and lambda, and solve the 3 equations to find all suspicious points, I calculate the function value of them all and see which is smallest and which is largest.

I don't know what I should do with the second constraint:

\[-1\leqslant x\leq 2\]

should I simply verify that each point satisfy this condition, or should I check some boundary points ?
 
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What I would do here is identify the objective function:

$$f(x,y)=xy^2$$

and the constraint:

$$g(x,y)=x-4y-1=0$$

And using Lagrange we ultimately find the critical points:

$$(x,y)=(1,0),\,\left(\frac{1}{3},-\frac{1}{6}\right)$$

Both points have $x$-values within the second constraint. Now, using the $x$-boundaries of the second constraint, we obtain two more critical points:

$$(x,y)=\left(-1,-\frac{1}{2}\right),\,\left(2,\frac{1}{4}\right)$$

So, you have 4 critical points at which to evaluate the objective function, and the smallest and largest values are your minimum and maximum respectively. What do you find?

Doing this, I get values that agree with W|A (if you account for approximations being done by W|A):

optimize x*y^2 subject to x-4y=1,-1<=x<=2
 

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