Boundary considerations in extremum problems

In summary, the conversation discusses whether it is necessary to evaluate boundary situations when finding maxima/minima, even when it is obvious that the extremum will not be on the boundary. It is recommended to solve the boundary conditions, but it is acceptable to include a simple proof that the function is uniformly zero on the boundary. Additionally, the question of taking the limit of x, y, and z to infinity is raised, with an example provided for further clarification.
  • #1
silver-rose
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0

Homework Statement


We are given a word problem and asked find maxima/minima (ie a simple example would be to find the least amount surface area required to build a box of a given volume).

Is it necessary to explicitly show that the relative interior max/min, calculated by setting the gradient to 0, is also the absolute extremum by evaluating possible extrema on the boundaries of the domain of the function, even when the physical considerations of the problem render it blatantly obvious that considering the boundaries will not yield a reasonable answer?

For example, for the aforementioned box problem,

x = length of box
y = width of box
z = height of box

The Domain of the box is

D --> { x,y,z : x [tex]\geq0[/tex], y[tex]\geq0[/tex], z[tex]\geq0[/tex] }

Must we explicitly evaluate boundary situations for when x=0 , y=0, z=0 ? (In this case, we see immediately that the volume will be 0) What about for the cases where x is large?

Do I also need to take the limit of x, y, and z to infinity?
 
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  • #2
silver-rose said:
Is it necessary to explicitly show that the relative interior max/min, calculated by setting the gradient to 0, is also the absolute extremum by evaluating possible extrema on the boundaries of the domain of the function, even when the physical considerations of the problem render it blatantly obvious that considering the boundaries will not yield a reasonable answer?
You should solve the boundary conditions, however simple. In a case where it is blatantly obvious that the extrema are not on the boundary, you may include a simple proof that, for example, the function is uniformly zero on the boundary, but positive on an interior point.
Do I also need to take the limit of x, y, and z to infinity?
This is a good question. Suppose you are asked to maximize f(x) = x2 over x > 0. Obviously, there is no maximum. Then, you have a choice between stating that f has no maximum, and stating that f is maximized when x becomes infinite.
 

Related to Boundary considerations in extremum problems

1. What are boundary conditions in extremum problems?

Boundary conditions in extremum problems refer to the constraints or limitations placed on the variables in the problem. These conditions define the boundaries within which the optimal solution must lie.

2. How do boundary conditions affect extremum problems?

Boundary conditions play a crucial role in extremum problems as they restrict the possible solutions and help to narrow down the search for the optimal solution. They also help to ensure that the solution is feasible and realistic.

3. What are the different types of boundary conditions in extremum problems?

There are three main types of boundary conditions in extremum problems: fixed, free, and mixed. Fixed boundary conditions specify a specific value for a variable, while free boundary conditions allow the variable to take any value within a range. Mixed boundary conditions involve a combination of fixed and free conditions.

4. How do you incorporate boundary conditions in extremum problems?

Incorporating boundary conditions in extremum problems typically involves adding them as constraints in the problem formulation. These constraints can be inequalities or equalities and are used to limit the possible solutions to those that satisfy the given boundary conditions.

5. What happens if the boundary conditions are not satisfied in an extremum problem?

If the boundary conditions are not satisfied, it means that the solution does not lie within the specified boundaries and is therefore not feasible. In such cases, the problem may need to be reformulated or additional constraints may need to be added to ensure that the solution meets the given boundary conditions.

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