MHB Are the critical points minima or maxima?

Click For Summary
SUMMARY

The function \( f(x_1, x_2) = 2 - x_1 - x_2 \) is analyzed for critical points under the constraint \( x_1^2 + x_2^2 = 8 \) using the Lagrange multiplier method. The critical points identified are \( (-2, -2) \) and \( (2, 2) \). Evaluating the function at these points yields a minimum value of \( f_{\min} = -2 \) at \( (2, 2) \) and a maximum value of \( f_{\max} = 6 \) at \( (-2, -2) \). The linear nature of the objective function indicates that no saddle points exist without additional constraints.

PREREQUISITES
  • Understanding of Lagrange multipliers
  • Familiarity with critical points in multivariable calculus
  • Knowledge of evaluating functions under constraints
  • Basic concepts of linear functions and their properties
NEXT STEPS
  • Study the method of Lagrange multipliers in greater detail
  • Learn about second derivative tests for identifying maxima and minima
  • Explore the implications of cyclical symmetry in optimization problems
  • Investigate the characteristics of linear functions in multivariable contexts
USEFUL FOR

Students and professionals in mathematics, particularly those focusing on calculus and optimization techniques, as well as anyone interested in applying Lagrange multipliers to solve constrained optimization problems.

mathmari
Gold Member
MHB
Messages
4,984
Reaction score
7
Hey! :o

We have the function $f(x_1, x_2)=2-x_1-x_2$ and we want to check if it has maxima or minima under the constraint $x_1^2+x_2^2=8$. Since we cannot solve for one variable at the equationof the constraint, we have to use the Langrange function, right? (Wondering)

I have done the following:

Let $g(x_1, x_2)=x_1^2+x_2^2-8$.

  • \begin{equation*}L(x_1,x_2,\lambda )=2-x_1-x_2 -\lambda \cdot \left (x_1^2+x_2^2-8\right )\end{equation*}
  • \begin{align*}&L_{x_1}(x_1,x_2,\lambda)=-1 -2x_1\lambda \\ & L_{x_2}(x_1,x_2,\lambda)=-1 -2x_2\lambda \\ & L_{\lambda}(x_1,x_2,\lambda)=- \left (x_1^2+x_2^2-8\right )\end{align*}
  • \begin{align*}&L_{x_1}(x_1,x_2,\lambda)=0 \Rightarrow -1 -2x_1\lambda=0 \\ & L_{x_2}(x_1,x_2,\lambda)=0 \Rightarrow -1 -2x_2\lambda=0 \\ & L_{\lambda}(x_1,x_2,\lambda)=0 \Rightarrow =- \left (x_1^2+x_2^2-8\right )=0\end{align*}
  • From the first equation we have that \begin{equation*}2x_1\lambda=-1 \Rightarrow \lambda=-\frac{1}{2x_1} \end{equation*}

    Replacing this in the second equation we get \begin{equation*}-1 -2x_2\left (-\frac{1}{2x_1}\right )=0 \Rightarrow -1 +\frac{x_2}{x_1}=0 \Rightarrow \frac{x_2}{x_1}=1 \Rightarrow x_2=x_1 \end{equation*}

    Since $x_2=x_1$ from the third equation we get \begin{equation*}x_1^2+x_1^2-8=0 \Rightarrow 2x_1^2=8 \Rightarrow x_1^2=4 \Rightarrow x_1=\pm 2\end{equation*}

    Therefore we get that's $({x_1}_0, {x_2}_0)=(-2,-2)$ und $({x_1}_0, {x_2}_0)=(2,2)$.

    For ${x_1}_0=-2$ we get $\lambda=\frac{1}{x_1}=-\frac{1}{2}$ and for ${x_1}_0=2$ we get $\lambda=\frac{1}{x_1}=\frac{1}{2}$. So, the critical points are $(-2,-2)$ und $(2,2)$.
Since the partial derivatives of second order are zero, we cannot use the condition
\begin{equation*}f_{x_1x_1}(x_0, y_0)\left\{\begin{matrix}
<0\\
>0
\end{matrix}\right. \ \text{ and } \ f_{x_1x_1}(x_0, y_0)f_{x_2x_2}(x_0, y_0)-\left (f_{x_1x_2}(x_0, y_0)\right )^2>0\end{equation*} to check if we have maxima or minima.

What can we do then in tis case? (Wondering)
 
Physics news on Phys.org
What I would do is observe that we have cyclical symmetry, that is we may interchange $x_1$ and $x_2$ with no change in either the objective function or the constraint, so we know the critical points are:

$$(-2,-2),\,(2,2)$$

Since:

$$f(-2,-2)=6$$ and $$f(2,2)=-2$$

we may therefore conclude:

$$f_{\min}=f(2,2)=-2$$

$$f_{\max}=f(-2,-2)=6$$
 
MarkFL said:
What I would do is observe that we have cyclical symmetry, that is we may interchange $x_1$ and $x_2$ with no change in either the objective function or the constraint, so we know the critical points are:

$$(-2,-2),\,(2,2)$$

Since:

$$f(-2,-2)=6$$ and $$f(2,2)=-2$$

we may therefore conclude:

$$f_{\min}=f(2,2)=-2$$

$$f_{\max}=f(-2,-2)=6$$

Ah ok. So, it cannot be that we have a saddle point? (Wondering)
 
mathmari said:
Ah ok. So, it cannot be that we have a saddle point? (Wondering)

The objective function is linear, so it describes a plane, and so I don't believe there will be any saddle points, or in fact any critical points without some kind of constraint imposed. :D
 
MarkFL said:
The objective function is linear, so it describes a plane, and so I don't believe there will be any saddle points, or in fact any critical points without some kind of constraint imposed. :D

I see! Thank you very much! (Happy)
 
Relativistic Momentum, Mass, and Energy Momentum and mass (...), the classic equations for conserving momentum and energy are not adequate for the analysis of high-speed collisions. (...) The momentum of a particle moving with velocity ##v## is given by $$p=\cfrac{mv}{\sqrt{1-(v^2/c^2)}}\qquad{R-10}$$ ENERGY In relativistic mechanics, as in classic mechanics, the net force on a particle is equal to the time rate of change of the momentum of the particle. Considering one-dimensional...

Similar threads

  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
1
Views
3K