Finding Max/Min Values on Functions of 3 Variables, Bounded by Ellipsoids

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SUMMARY

The discussion focuses on finding the absolute minimum and maximum values of the function F(x,y,z) = x² - 2x - y² + z², constrained by the ellipsoid G(x,y,z) = x² + 4y² + z² = 4. The solution employs Lagrange multipliers, leading to critical points at (-2,0,0) for the maximum value of 8 and (4/5, ±√21/5, 0) for the minimum value of -9/5. The analysis confirms that the critical points derived from the gradients of F and G are valid, and the results align with the constraints of the ellipsoid.

PREREQUISITES
  • Understanding of multivariable calculus, specifically Lagrange multipliers
  • Familiarity with the concept of gradients in vector calculus
  • Knowledge of ellipsoidal equations and their geometric implications
  • Ability to evaluate functions at critical points
NEXT STEPS
  • Study the application of Lagrange multipliers in optimization problems
  • Learn about the geometric interpretation of gradients and level surfaces
  • Explore the properties of ellipsoids and their equations in three dimensions
  • Investigate the behavior of functions under constraints using numerical methods
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Students and professionals in mathematics, particularly those studying optimization techniques, multivariable calculus, and geometric constraints. This discussion is beneficial for anyone looking to deepen their understanding of constrained optimization problems.

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Homework Statement


Find the absolute minimum and maximum of F(x,y,z) = x2 - 2x - y2 + z2 on the ellipsoid G(x,y,z) = x2 + 4y2 + z2 = 4

Homework Equations


The Attempt at a Solution


I was thinking of trying to solve this by using Lagrange multipliers. So, finding the gradients:

Fx = 2x - 2 = Gx = λ 2x
Fy = - 2y = Gy = λ 8y
Fz = 2z = Gz = λ 2z

From the first partial derivative I have 2x - 2 - λ2x = 0, which suggests x = 1/(1-λ). From the second partial derivative I have y(-2 - λ * 8) = 0, which suggests y = 0. Similarly, from the third partial derivative I have z(2 - λ * 2) = 0, which suggests z = 0. From G(1/(1-λ),0,0) I get λ = ((-/+) 1/2) + 1, or λ = 1/2 or 3/2.

Therefore, x = -2 or 2. Evaluating F(-2,0,0) = 8 and F(2,0,0) = 0. So, (-2,0,0) is our max and (2,0,0) is our min.

Does that sound about right?
 
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The two equations may suggest a variable is 0 but it doesn't follow that it must be! However, you can argue that if y is not 0, then, dividing both sides of the second equation by y, \lambda= -1/4. Similarly, if z is not 0, \lambda= 1. If \lambda= 1, the first equation cannot be satisfied but if \lambda= -1/4 the first equation gives x= 4/5. Putting x= 4/5, z= 0 into x^2+ 4y^2+ z^2= 4 gives 16/25+ 4y^2= 4 so y^2= 84/25 and then y= 2\sqrt{21}/5. (4/5, 2\sqrt{21}/5, 0) also satisfies those equations. What is F(4/5, 2\sqrt{21}/5, 0)?
 
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HallsofIvy said:
The two equations may suggest a variable is 0 but it doesn't follow that it must be! However, you can argue that if y is not 0, then, dividing both sides of the second equation by y, \lambda= -1/4. Similarly, if z is not 0, \lambda= 1. If \lambda= 1, the first equation cannot be satisfied but if \lambda= -1/4 the first equation gives x= 4/5. Putting x= 4/5, z= 0 into x^2+ 4y^2+ z^2= 4 gives 16/25+ 4y^2= 4 so y^2= 84/25 and then y= 2\sqrt{21}/5. (4/5, 2\sqrt{21}/5, 0) also satisfies those equations. What is F(4/5, 2\sqrt{21}/5, 0)?

Do you mean y = ± √(21)/5, because 16/25 + 4(2sqrt(21)/5)^2 ≠ 4. Anyway, presuming this is what you meant, I have to test the points (2,0,0), (-2,0,0), (4/5,sqrt(21)/5,0), (4/5,-sqrt(21)/5,0).

F(2,0,0) = 0
F(-2,0,0) = 8
F(4/5,sqrt(21)/5,0) = -9/5
F(4/5,-sqrt(21)/5,0) = -9/5

Therefore, my max is at (-2,0,0) and is 8. My minimums are at (4/5,sqrt(21)/5,0) and (4/5,-sqrt(21)/5,0) and are -9/5.

Sound about right?
 

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