Holly's questions at Yahoo Answers regarding Lagrange multipliers

In summary, we used Lagrange multipliers to find the extrema of two constrained optimization problems involving positive variables. For the first problem, we minimized the objective function $f(x,y)=x^2+y^2$ subject to the constraint $x+2y-20=0$, obtaining a minimum of $f_{\min}=80$ at the critical point $(x,y)=(4,8)$. For the second problem, we maximized the objective function $f(x,y)=\sqrt{99-x^2-y^2}$ subject to the constraint $x+y-10=0$, obtaining a maximum of $f_{\max}=7$ at the critical point $(x,y)=(5,5)$.
  • #1
MarkFL
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Here are the questions:

Calculus 3 Lagrange multipliers help?


Okay I CANNOT figure out lagrange multipliers. Can anyone help me with my homework problems? Thanks!

1.

Use Lagrange multipliers to find the indicated extrema, assuming that x and y are positive.
minimize f(x,y)= x^2 + y ^2
constraint: x+ 2y - 20 = 0

2.
Use Lagrange multipliers to find the indicated extrema, assuming that x and y are positive.

Maximize f(x,y) = (99 - x^2 - y^2)^(1/2)
constraint: x + y - 10 = 0

I have posted a link there to this thread so the OP can view my work.
 
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  • #2
Hello Holly,

1.) We are given the objective function:

\(\displaystyle f(x,y)=x^2+y^2\)

subject to the constraint:

\(\displaystyle g(x,y)=x+2y-20=0\)

Lagrange multipliers gives rise then to the following system:

\(\displaystyle 2x=\lambda(1)\)

\(\displaystyle 2y=\lambda(2)\)

This implies:

\(\displaystyle \lambda=2x=y\)

Substituting for $y$ into the constraint, we find:

\(\displaystyle x+2(2x)-20=0\implies x=4\implies y=8\)

Thus, we obtain the critical point:

\(\displaystyle (x,y)=(4,8)\)

The objective function's value at this point is:

\(\displaystyle f(4,8)=4^2+8^2=80\)

To ensure this is a minimum, let's evaluate the objective function at another point on the constraint, such as \(\displaystyle (x,y)=(2,9)\):

\(\displaystyle f(2,9)=2^2+9^2=85\)

And so we may now conclude:

\(\displaystyle f_{\min}=f(4,8)=80\)

2.) We are given the objective function:

\(\displaystyle f(x,y)=\sqrt{99-x^2-y^2}\)

subject to the constraint:

\(\displaystyle g(x,y)=x+y-10=0\)

Now here we see that $x$ and $y$ have cyclic symmetry, that is, we may switch the two variables and still have the same objective function and constraint. Thus we know the critical value may be obtained when $x=y$. The constraint then gives us:

\(\displaystyle x=y=5\)

And so our critical point is:

\(\displaystyle (x,y)=(5,5)\)

The objective function's value at this point is:

\(\displaystyle f(5,5)=\sqrt{99-5^2-5^2}=7\)

To ensure this is a maximum, let's evaluate the objective function at another point on the constraint, such as \(\displaystyle (x,y)=(4,6)\):

\(\displaystyle f(5,5)=\sqrt{99-4^2-6^2}=\sqrt{47}<7\)

And so we may conclude:

\(\displaystyle f_{\max}=f(5,5)=7\)
 

FAQ: Holly's questions at Yahoo Answers regarding Lagrange multipliers

1. What are Lagrange multipliers?

Lagrange multipliers are mathematical tools used in optimization problems to find the maximum or minimum value of a function while satisfying a set of constraints. They can be used to solve problems in a variety of fields, including physics, economics, and engineering.

2. How do Lagrange multipliers work?

Lagrange multipliers work by introducing a new variable, known as a multiplier, into the optimization problem. The multiplier is then used to create a new function, known as the Lagrangian, which includes both the original function and the constraints. The maximum or minimum value of the Lagrangian occurs at the same point as the maximum or minimum value of the original function, but with the added constraint that the gradient of the Lagrangian must be equal to zero.

3. When should I use Lagrange multipliers?

Lagrange multipliers are useful when trying to optimize a function subject to a set of constraints. This can include problems such as finding the minimum cost to produce a certain number of products, or maximizing profit while staying within a budget. They are also helpful in finding critical points in multivariable functions.

4. What are the limitations of Lagrange multipliers?

While Lagrange multipliers are powerful tools, they do have some limitations. They can only be used for problems with smooth functions and constraints, and may not work for non-convex problems. They also require the constraints to be independent, meaning that one constraint cannot be a combination of other constraints.

5. Are there any applications of Lagrange multipliers in real life?

Yes! Lagrange multipliers have many practical applications in fields such as economics, engineering, and physics. For example, they can be used to optimize resource allocations, design efficient transportation routes, or determine the minimum amount of material needed to construct a structure. They are also used in machine learning algorithms and in solving differential equations.

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