Respuesta :
Answer:
The dimensions are, base [tex]b=\sqrt[3]{200}[/tex], depth [tex]d=\sqrt[3]{200}[/tex] and height [tex]h=\sqrt[3]{200}[/tex].
Step-by-step explanation:
First we have to understand the problem, we have a box of unknown dimensions (base [tex]b[/tex], depth [tex]d[/tex] and height [tex]h[/tex]), and we want to optimize the used material in the box. We know the volume [tex]V[/tex] we want, how we want to optimize the card used in the box we need to minimize the Area [tex]A[/tex] of the box.
The equations are then, for Volume
[tex]V=200cm^3 = b.h.d[/tex]
For Area
[tex]A=2.b.h+2.d.h+2.b.d[/tex]
From the Volume equation we clear the variable [tex]b[/tex] to get,
[tex]b=\frac{200}{d.h}[/tex]
And we replace this value into the Area equation to get,
[tex]A=2.(\frac{200}{d.h} ).h+2.d.h+2.(\frac{200}{d.h} ).d[/tex]
[tex]A=2.(\frac{200}{d} )+2.d.h+2.(\frac{200}{h} )[/tex]
So, we have our function [tex]f(x,y)=A(d,h)[/tex], which we have to minimize. We apply the first partial derivative and equalize to zero to know the optimum point of the function, getting
[tex]\frac{\partial A}{\partial d} =-\frac{400}{d^2}+2h=0[/tex]
[tex]\frac{\partial A}{\partial h} =-\frac{400}{h^2}+2d=0[/tex]
After solving the system of equations, we get that the optimum point value is [tex]d=\sqrt[3]{200}[/tex] and [tex]h=\sqrt[3]{200}[/tex], replacing this values into the equation of variable [tex]b[/tex] we get [tex]b=\sqrt[3]{200}[/tex].
Now, we have to check with the hessian matrix if the value is a minimum,
The hessian matrix is defined as,
[tex]H=\left[\begin{array}{ccc}\frac{\partial^2 A}{\partial d^2} &\frac{\partial^2 A}{\partial d \partial h}\\\frac{\partial^2 A}{\partial h \partial d}&\frac{\partial^2 A}{\partial p^2}\end{array}\right][/tex]
we know that,
[tex]\frac{\partial^2 A}{\partial d^2}=\frac{\partial}{\partial d}(-\frac{400}{d^2}+2h )=\frac{800}{d^3}[/tex]
[tex]\frac{\partial^2 A}{\partial h^2}=\frac{\partial}{\partial h}(-\frac{400}{h^2}+2d )=\frac{800}{h^3}[/tex]
[tex]\frac{\partial^2 A}{\partial d \partial h}=\frac{\partial^2 A}{\partial h \partial d}=\frac{\partial}{\partial h}(-\frac{400}{d^2}+2h )=2[/tex]
Then, our matrix is
[tex]H=\left[\begin{array}{ccc}4&2\\2&4\end{array}\right][/tex]
Now, we found the eigenvalues of the matrix as follow
[tex]det(H-\lambda I)=det(\left[\begin{array}{ccc}4-\lambda&2\\2&4-\lambda\end{array}\right] )=(4-\lambda)^2-4=0[/tex]
Solving for[tex]\lambda[/tex], we get that the eigenvalues are: [tex]\lambda_1=2[/tex] and [tex]\lambda_2=6[/tex], how both are positive the Hessian matrix is positive definite which means that the function[tex]A(d,h)[/tex] is minimum at that point.