Optimize f(x,y,z) = 2x + 2y + 2z

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In summary, the conversation discusses the optimization of a function with two constraints. The process involves finding critical points using the Lagrange multiplier method and then substituting the values back into the equations to find the optimal points. The values of \lambda and \mu can also be found if desired.
  • #1
squenshl
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Optimize f(x,y,z) = 2x + 2y + 2z subject to constraints g(x,y,z) = x2 - y2 - z2 - 1 = 0 & h(x,y,z) = x2 + y2 + z2 - 17 = 0.

I found Lx = 2 + 2[tex]\lambda[/tex]x - 2[tex]\mu[/tex]x = 0, Ly = 2 + 2[tex]\lambda[/tex]y - 2[tex]\mu[/tex]y = 0 & Lz = 2 + 2[tex]\lambda[/tex]z - 2[tex]\mu[/tex]z = 0
I'm just asking how to use Lx, Ly & Lz to eliminate [tex]\lambda[/tex] & [tex]\mu[/tex] to get the critical points.
 
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  • #2


Your "Lx" is incorrect. Because x2 is positive in both f and g, it should be [itex]2+ 2\lambda x+ 2\mu x= 0[/itex]

Those reduce very easily to [itex](\mu+ \lambda)x= -1[/itex], [itex](\mu- \lambda)y= -1[/itex] and [itex](\mu- \lambda)z= -1[/itex]. Also, just adding the two constraints eliminates both y and z giving [itex]2x^2- 18= 0[/itex] so [itex]x= \pm 3[/itex]. Divide the second equation by the third to get y/z= 1 so y= z. Put that into [itex]x^2- y^2- z^2- 1= 0[/itex] to get [itex]9- 2z^2= 1[/itex] so [itex]2z^2= 8[/itex] and [itex]z= \pm 2[/itex]. The function is optimized at (3, 2, 2), (-3, 2, 2), (3, -2, -2), and (-3, -2, -2).
 
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  • #3


But I thought L(x,y,z,[tex]\lambda[/tex],[tex]\mu[/tex]) = 2x + 2y + 2z - [tex]\lambda[/tex](x2 - y2 - z2 - 1) - [tex]\mu[/tex](x2 + y2 + z2 - 17) making x2 both negative making Lx = 2 - 2[tex]\lambda[/tex]x - 2[tex]\mu[/tex]x. But I don't think it matters in the end result.
 
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  • #4


What if I wanted to find [tex]\lambda[/tex] & [tex]\mu[/tex]?
 
  • #5


squenshl said:
But I thought L(x,y,z,[tex]\lambda[/tex],[tex]\mu[/tex]) = 2x + 2y + 2z - [tex]\lambda[/tex](x2 - y2 - z2 - 1) - [tex]\mu[/tex](x2 + y2 + z2 - 17) making x2 both negative making Lx = 2 - 2[tex]\lambda[/tex]x - 2[tex]\mu[/tex]x. But I don't think it matters in the end result.
It just changes the values of [itex]\lambda[/itex] and [itex]\mu[/itex].

squenshl said:
What if I wanted to find [tex]\lambda[/tex] & [tex]\mu[/tex]?
Why would you? They are never part of the original problem. But if you do, once you have found x, y, and z, you can substitute those back into the equations to find [itex]\lambda[/itex] and [itex]\mu[/itex].
 

1. What does the function f(x,y,z) = 2x + 2y + 2z represent?

The function f(x,y,z) = 2x + 2y + 2z represents a linear equation with three variables, x, y, and z. It calculates the sum of twice the values of each variable.

2. What is the purpose of optimizing this function?

The purpose of optimizing this function is to find the values of x, y, and z that will result in the maximum or minimum value of the function, depending on the specific problem or application.

3. How do you find the optimal values for x, y, and z in this function?

To find the optimal values for x, y, and z, you can use various mathematical techniques such as taking partial derivatives, setting them equal to zero, and solving for the variables. Other methods include using gradient descent or optimization algorithms.

4. Can this function be optimized with more than three variables?

Yes, this function can be optimized with more than three variables. However, as the number of variables increases, the complexity of the problem also increases.

5. What are some real-life applications of optimizing a function like f(x,y,z) = 2x + 2y + 2z?

Optimizing functions like f(x,y,z) = 2x + 2y + 2z can be used in various fields such as economics, engineering, and physics. For example, in economics, it can be used to maximize profits by determining the optimal prices for products. In engineering, it can be used to optimize the design of a structure or system. In physics, it can be used to find the path that minimizes the time or energy required for an object to move from one point to another.

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