Maximizing xy with Given Constraints: [SOLVED]

In summary, the conversation discusses finding the maximum value of xy given that x is in the range of 1 to 2, y is in the range of -1 to 1, and x + y = 0. The participants explore different methods, such as using derivatives and Lagrange multipliers, but ultimately realize that the maximum value of xy is 0 when x and y are both 0. They also note that this problem may be too easy for Lagrange multipliers and that the maximum value is negative for all other values of x and y.
  • #1
rohanprabhu
414
2
[SOLVED] Maximum value of xy

Homework Statement



Q] Given that [itex]x \in [1, 2][/itex] and [itex]y \in [-1, 1][/itex] and [itex]x + y = 0[/itex], find the maximum value of [itex]xy[/itex]

The Attempt at a Solution


I have no idea at all. Does this have something to do with the maxima/minima. In that case, i can get that:

[tex]
\frac{dx}{dy} = xdy + ydx
[/tex]

also,
[tex]
dx = -dy
[/tex]

hence, for the condition of [itex]f'(x) = 0[/itex],

[tex]
xdy + ydx = 0
[/tex]

[tex]
xdy = - ydx
[/tex]

[tex]
\frac{dy}{dx} = \frac{-y}{x}
[/tex]

i don't even know what I'm doing till now.
 
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  • #2
If f = xy, and x + y = 0, then f = -x^2. I think it should be fairly straight forward to find the maximum value of this function. Of course if this is not in the region for which the function is defined, then you just need to check at the boundaries.
 
  • #3
This looks like a problem too easy for Lagrange multipliers, so I'll keep it simple. In case you don't know, [itex]u[/itex] is defined to be [itex]xy[/itex], so that's what we want to maximize.
[tex]x+y=0 \Rightarrow y=-x[/tex]
[tex]u=xy=-x\times x=-x^2[/tex]
Take the derivative and set to zero,
[tex]\frac{du}{dx}=0=-2x\Rightarrow x=0 \Rightarrow y=0[/tex]
This makes sense because it's going to be the product of a negative number and its absolute value. So the largest is going to be at zero.
 
  • #4
In fact you don't need to differentiate at all. Once you realize that u(x)= -x2, it is clear that u is negative for all x except x= 0.
 
  • #5
Perhaps it may be solved by Lagrange multiplier, you should obtain the minimum of

[tex] xy-{\lambda}(x+y) [/tex]

differenentiating respect to x , y and lambda we get the equations

[tex] y-{\lambda}=0 [/tex]

[tex] x-{\lambda}=0 [/tex]

[tex] x+y=0 [/tex]

it seems that only a minimum at x=y=0 exists , no maximum.
 
  • #6
thanks to everybody.. i got it now. I really feel stupid about this problem. I have no idea about Lagrange multiplier, but calculating f(x) is something i should've done... thanks to everyone again.
 

1. What is the purpose of maximizing xy with given constraints?

The purpose of maximizing xy with given constraints is to find the maximum value of the product xy while staying within certain limitations or restrictions. This problem is commonly encountered in optimization and mathematical modeling.

2. What are some common types of constraints in maximizing xy?

Some common types of constraints in maximizing xy include budget constraints, resource constraints, and physical constraints such as size or weight limitations. These constraints help to narrow down the possible solutions and make the optimization problem more realistic.

3. How do you solve a problem involving maximizing xy with given constraints?

The most common approach to solving a problem involving maximizing xy with given constraints is to use mathematical techniques such as Lagrange multipliers or the simplex method. These methods involve setting up an objective function and then using constraints to find the optimal solution.

4. What are some real-life applications of maximizing xy with given constraints?

Maximizing xy with given constraints has many real-life applications, including production planning, portfolio optimization, and resource allocation. It can also be applied to various fields such as engineering, economics, and business management.

5. What are some tips for effectively maximizing xy with given constraints?

Some tips for effectively maximizing xy with given constraints include carefully defining the objective function, clearly stating the constraints, and considering all possible solutions. It is also important to regularly check and adjust the constraints to ensure that the optimal solution is still valid.

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