Lagrange Multipliers with Multiple Constraints?

In summary: These values of λ and μ are the max and min values of f.In summary, The homework statement is: Lagrange multipliers can be used to solve a system of equations in order to find the max and min values of a function.
  • #1
AimlessWander
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Homework Statement



Using Lagrange multipliers, find the max and the min values of f:

f(x,y,z) = x^2 +2y^2+3x^2

Constraints:

x + y + z =1
x - y + 2z = 2

Homework Equations



∇f(x) = λ∇g(x) + μ∇h(x)

The Attempt at a Solution



Using Lagrange multipliers, I obtained the equations:

2x = λ + μ
4y = λ - μ
6z = λ + 2μ

With the constraints, I tried to find values for the unknowns, but I can't solve the system of equations. I don't know where to go from here. Can anyone help put? Any input is appreciated!
 
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  • #2
AimlessWander said:

Homework Statement



Using Lagrange multipliers, find the max and the min values of f:

f(x,y,z) = x^2 +2y^2+3x^2

Constraints:

x + y + z =1
x - y + 2x = 2


Homework Equations



∇f(x) = λ∇g(x) + μ∇h(x)


The Attempt at a Solution



Using Lagrange multipliers, I obtained the equations:

2x = λ + μ
4y = λ - μ
6z = λ + 2μ

With the constraints, I tried to find values for the unknowns, but I can't solve the system of equations. I don't know where to go from here. Can anyone help put? Any input is appreciated!

Your equations give you x, y and z in terms of λ and μ. Plug these expressions into the two constraint equations to get two equations for the two unknowns λ, μ.
 
  • #3
Hey, thanks for helping out! Please note the small change in the second constraint equation: it's x -y + 2z = 2. I did exactly that, but it didn't really seem to help solve for the unknowns. By plugging in the expressions obtained into the constraint equations, I got 11λ + 7μ = 12 and 7λ+ 17μ = 24. Solving, I still get an equation with two unknowns.
 
  • #4
AimlessWander said:
Hey, thanks for helping out! Please note the small change in the second constraint equation: it's x -y + 2z = 2. I did exactly that, but it didn't really seem to help solve for the unknowns. By plugging in the expressions obtained into the constraint equations, I got 11λ + 7μ = 12 and 7λ+ 17μ = 24. Solving, I still get an equation with two unknowns.

I don't understand what you mean. When you solve the two equations you will get two numbers, one for λ and one for μ. If that is not what you get you had better show the details here.

BTW: you wrote f(x,y,z) = x^2 +2y^2+3x^2, but I assume you meant 3z^2 in the last term.
 
  • #5
Altogether you have 5 equations in 5 unknowns x, y, z, λ, and μ: the two constraint equations, and the three equations you have derived.

There are lots of ways to solve them (some quicker than others) but you certainly have enough equations to get the solution.

You don't need the values of λ and μ to get the max and min values of f, but as Ray Vickson said it's probably easiest to find λ and μ first, and then find x y and z.
 
  • #6
With [itex]2x= \lambda+ \mu[/itex], [itex]2y= \lambda-\mu[/itex], and [itex]2z= \lambda+ 2\mu[/itex] the two constraints become [itex]x+ y+ z= (\lambda + \mu)/2+ (\lambda- \mu)/2+ (\lambda+ 2\mu)/2= 1[/itex], which reduces to [itex]3\lambda+ 2\mu= 2[/itex], and [itex]x- y+ 2z= (\lambda+ \mu)/2- (\lambda- \mu)/2+ 2(\lambda+ 2\mu)/2= 2[/itex], which reduces to [itex]\lambda+ 2\mu= 2[/itex].

Solve [itex]3\lambda+ 2\mu= 2[/itex] and [itex]\lambda+ 3\mu= 2[/itex].
 

FAQ: Lagrange Multipliers with Multiple Constraints?

What are Lagrange multipliers with multiple constraints?

Lagrange multipliers with multiple constraints is a mathematical technique used to find the maximum or minimum values of a multivariable function subject to multiple constraints. It involves using a system of equations, known as Lagrange equations, to find critical points where the gradient of the function is equal to the gradient of the constraints.

When should Lagrange multipliers with multiple constraints be used?

Lagrange multipliers with multiple constraints should be used when optimizing a multivariable function subject to multiple constraints. This is useful in many fields of science, such as economics, physics, and engineering, where a certain quantity needs to be maximized or minimized while satisfying multiple constraints.

What is the main advantage of using Lagrange multipliers with multiple constraints?

The main advantage of using Lagrange multipliers with multiple constraints is that it simplifies the optimization process by reducing it to a system of equations. This allows for a more straightforward and efficient solution compared to other methods, such as substitution or elimination.

What are the limitations of using Lagrange multipliers with multiple constraints?

One limitation of using Lagrange multipliers with multiple constraints is that it can only be applied to functions that are continuous and have continuous derivatives. Additionally, it can be computationally expensive for functions with a large number of variables and constraints.

Are there any real-world applications of Lagrange multipliers with multiple constraints?

Yes, Lagrange multipliers with multiple constraints have many real-world applications, such as in the design of optimal structures in engineering, minimizing costs in economics, and finding the optimal path for a moving object in physics. It is also widely used in machine learning and optimization problems in computer science.

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