Extrema of a multivariable function

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SUMMARY

The discussion focuses on proving that among all parallelograms with a fixed perimeter \( l \), a square with sides of length \( \frac{l}{4} \) has the maximum area. This is established using the second partials test, defined by \( D = f_{xx}f_{yy} - f_{xy}^{2} \), and the method of Lagrange multipliers, represented by \( \nabla f = \lambda \nabla g \). The area of the parallelogram is expressed as \( A = ab \sin \phi \), and it is concluded that the maximum area occurs when \( a = b \) and \( \phi = \frac{\pi}{2} \), confirming the square configuration.

PREREQUISITES
  • Understanding of multivariable calculus concepts, specifically the second partials test.
  • Familiarity with Lagrange multipliers for optimization problems.
  • Knowledge of trigonometric functions and their application in geometry.
  • Ability to manipulate equations involving area and perimeter of geometric shapes.
NEXT STEPS
  • Study the application of the second partials test in multivariable optimization problems.
  • Learn more about the method of Lagrange multipliers and its applications in constrained optimization.
  • Explore the geometric properties of parallelograms and their area calculations.
  • Investigate the relationship between angles and side lengths in maximizing area for various geometric shapes.
USEFUL FOR

Students and educators in mathematics, particularly those studying calculus and optimization techniques, as well as anyone interested in geometric properties and their applications in real-world problems.

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Homework Statement


Show that among all parallelograms with perimeter [tex]l[/tex], a square with sides of length [tex]l/4[/tex] has maximum area. Do this using the second partials test, and then using Lagrange multipliers.


Homework Equations


Area of a parallelogram: [tex]A = absin\phi[/tex], where a and b are the lengths of two adjacent sides and [tex]\phi[/tex] is the angle between them.

Second partials test: [tex]D=f_{xx}f_{yy} - f_{xy}^{2}[/tex]

Method of Lagrange multipliers: [tex]\nabla f=\lambda\nabla g[/tex]

The Attempt at a Solution


To do it using the second partials test, I would have to reduce A to a function of two variables. I know this has to do with expressing [tex]\phi[/tex] as a function of [tex]a[/tex] and [tex]b[/tex]. After this, I'm stuck.

For the Lagrange multipliers method, I can use [tex]A(a,b)[/tex] as the function to be maximized and use [tex]g(a,b)= 2a + 2b - l[/tex] as the constraint equation. However, I'm still stuck on how to reduce [tex]A[/tex] to a function of two variables. Any help?
 
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Actually you don't really have to take [tex]\phi[/tex] into consideration. Can you show that one particular critical point occurs when a=b? So geometrically that reduces the possibilities to either a square or a rhombus. Since the area function you want to maximise is given by [tex]ab\sin \phi[/tex] and a=b, it's easy to tell that the expression is maxed when [tex]\phi = \frac{\pi}{2}[/tex].
 

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