Are the critical points minima or maxima?

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Discussion Overview

The discussion revolves around determining whether the critical points of the function $f(x_1, x_2)=2-x_1-x_2$ under the constraint $x_1^2+x_2^2=8$ are minima or maxima. The scope includes mathematical reasoning and the application of Lagrange multipliers.

Discussion Character

  • Mathematical reasoning
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant outlines the use of the Lagrange function to find critical points, deriving the points $(-2,-2)$ and $(2,2)$.
  • Another participant notes the cyclical symmetry of the problem and calculates the function values at the critical points, suggesting that $f_{\min}=-2$ and $f_{\max}=6$.
  • Some participants express uncertainty about the possibility of saddle points, with one arguing that the linear nature of the objective function implies no saddle points exist without constraints.

Areas of Agreement / Disagreement

There is no consensus on whether the critical points are minima or maxima, as some participants propose values while others question the existence of saddle points. The discussion remains unresolved regarding the classification of the critical points.

Contextual Notes

The discussion includes assumptions about the nature of the objective function and the implications of the constraint, which may affect the conclusions drawn about critical points.

mathmari
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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)
 
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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)
 

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