Is the Objective Function Always Nonnegative in Linear Optimization Problems?

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In summary, the conversation is about finding a solution for an objective function and constraints given a LOP P. The objective function is the most important part for the question, and the constraints are not given. The solution is shown to be y = (2t, 3t, t)^t for all t greater than or equal to 0. There is a discussion about the behavior of the objective function as t approaches infinity, and it is determined that it depends on whether t approaches positive or negative infinity. The flaw in the initial thinking is not considering t approaching both positive and negative infinity. The conversation also touches on the assumption that the objective function is always nonnegative, but it is questioned whether this is always true in theoretical presentations.
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flyingpig
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Homework Statement



Given the follow LOP P

I am just going to write down the obj function because that is most important for my question and the constraints aren't

[tex]w = y_1 - 2y_2 + y_3[/tex]

I was asked to show that [tex]y = (2t, 3t,t)^t[/tex] is a solution for all [tex]t\geq 0[/tex]

So w = 2t - 2(3t) +t = 2t - 6t + t = -4t + t = -3t

Now initally I thought that as [tex]t \to \infty [/tex], [tex]-3t \to -\infty [/tex]

I checked the key provided by my prof and he took [tex]t \to -\infty [/tex] and [tex]-3t \to \infty [/tex]

Is it because we always assume w >0?

The flaw I made is that I never consider [tex]t \to \pm \infty [/tex].




Homework Equations





The Attempt at a Solution

 
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In applied problems, the objective function is usually nonnegative, but in more theoretic presentations, I don't see why this needs to be true.
 
  • #3


Mark44 said:
In applied problems, the objective function is usually nonnegative, but in more theoretic presentations, I don't see why this needs to be true.

I asked my prof today and he kinda said the same thing about "yes intuitively that is right, we want obj f > 0". Then he added a bunch of things that confused me even more...

He stated something like this

max z = -min(-z)
 

FAQ: Is the Objective Function Always Nonnegative in Linear Optimization Problems?

What is a limit problem?

A limit problem is a mathematical concept that involves finding the value that a function approaches as the input approaches a certain value. It is used to describe the behavior of a function near a specific point.

How do you solve a limit problem?

To solve a limit problem, you can use various techniques such as direct substitution, factoring, and rationalization. It is also important to understand the properties and rules of limits, such as the limit laws and the Squeeze Theorem.

What is the importance of solving limit problems?

Solving limit problems helps us understand the behavior of functions and their graphs. It also has applications in various fields such as physics, engineering, and economics. Additionally, it is a fundamental concept in calculus and is essential for solving more complex problems.

What are some common mistakes to avoid when solving limit problems?

Some common mistakes to avoid when solving limit problems include forgetting to check for continuity, not considering the left and right limits separately, and using incorrect limit laws. It is also important to check for any algebraic errors and to simplify the expression as much as possible before taking the limit.

Can limits be used to solve real-world problems?

Yes, limits can be used to solve real-world problems such as finding the maximum or minimum value of a function, calculating rates of change, and determining the behavior of a system. They are also used in optimization problems, where the goal is to find the most efficient solution to a real-world problem.

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