How Do You Solve Lagrange Multipliers with Complex Constraints?

In summary, the conversation discusses using the method of Lagrange multipliers to find the minimum value of a function, subject to a constraint. The equations for the partial derivatives are given, and the constraint itself is mentioned as being necessary to solve the problem. The conversation also includes a step-by-step process for solving the equations and finding the values of x, y, and z in terms of Lambda. The idea of combining equations to eliminate terms is explained, and it is suggested to use basic simultaneous equation solving methods to solve the problem.
  • #1
kawsar
13
0
1. Use the method of Lagrange multipliers to nd the minimum value of
the function:
f(x,y,z) = xy + 2xz + 2yz

subject to the constraint xyz = 32.



I understand the method how Lagranges Multipliers is donw done but seem to have got stuck solving the Simultaneous Equations involving the Partial Derivatives involving [tex]\lambda[/tex].

I think the 3 Partial Derivatives (set equal to 0) are:

f[tex]_{x}[/tex]=y+2z-[tex]\lambda[/tex]yz=0
f[tex]_{y}[/tex]=x+2z-[tex]\lambda[/tex]xz=0
f[tex]_{z}[/tex]=2x+2y-[tex]\lambda[/tex]xy=0

Any chance helping me work out how I can solve x, y and z in terms of [tex]\lambda[/tex] OR if I've made an earlier mistake somewhere, sorting that out for me?

Thanks

edit: f[tex]_{x}[/tex] is supposed to be f sub x - Don't know how to write that with the editor.
 
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  • #2
Your forgot one equation (the constraint itself). This gives you 4 equations in 4 unknowns.
 
  • #3
Ok. You mean the constraint itself and not the partial derivative in respect to Lambda.

I'll see if that gets me anywhere. Thanks!
 
  • #4
Sorry guys... A few more pointers please! Don't know what's wrong with me but can't seem to solve the eqns for some reason...
 
  • #5
Here is how I solved it:

1. Combine 1st and 2nd equations to eliminate the term containing Lambda. Result is an expression relating x & y

2. Combine 1st and 3rd equations to eliminate the term containing Lambda. Result is an expression relating x and z

3. Use the above and the constraint equation and to solve for z

4. Use the value of z to find x & y
 
  • #6
Thanks! When you say combine do you mean write one equals the other and then try and simplify it? Could you do your step one please.
 
  • #7
kawsar said:
Thanks! When you say combine do you mean write one equals the other and then try and simplify it? Could you do your step one please.

The concept is basic Gauss elimination. Let's say you have the following:

2x + 3y = 5
x + 2y = 3

to eliminate the term with y, multiple the 1st equation by 2 and 2nd by 3:

4x + 6y = 10
3x + 6y = 9

Subtracting the 2nd from the 1st (i.e. combine) you get:

x = 1

Now apply the same idea to your situation to eliminate the term with Lambda.
 
Last edited:
  • #8
Hmmm... The first two formulae have 3 different variables and the Lambda. Will the basic Simultaneous Equation solving method work with that?
 
  • #9
kawsar said:
Hmmm... The first two formulae have 3 different variables and the Lambda. Will the basic Simultaneous Equation solving method work with that?

Worked for me. Try it.
 

Related to How Do You Solve Lagrange Multipliers with Complex Constraints?

What are Lagrange multipliers and why are they important in optimization?

Lagrange multipliers are a mathematical tool used in optimization problems to find the maximum or minimum value of a function subject to certain constraints. They are important because they allow us to solve constrained optimization problems without the need for trial and error methods.

How do Lagrange multipliers work?

Lagrange multipliers work by introducing a new variable called a multiplier to the original function and its constraints. This creates a new function, which can be solved using the method of partial derivatives to find the optimal solution.

What types of problems can be solved using Lagrange multipliers?

Lagrange multipliers can be used to solve both constrained and unconstrained optimization problems. They are also useful for solving problems involving multiple variables and complex constraints.

What are some common applications of Lagrange multipliers?

Lagrange multipliers have many applications in various fields of science and engineering, including economics, physics, and engineering. They can be used to optimize production processes, minimize energy consumption, and maximize profit.

Are there any limitations to using Lagrange multipliers?

Lagrange multipliers may not always provide the most efficient solution to an optimization problem. In some cases, other methods such as gradient descent may be more suitable. Additionally, the use of Lagrange multipliers can become computationally expensive for large and complex problems.

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