Given an NLO reduce it to unconstrained optimization problem

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Homework Help Overview

The problem involves minimizing the function x3 - x4^2 subject to two constraints: x1^2 + x3 = 2 and (x2 - x4)(x2 + x4) = 1. The context is nonlinear optimization (NLO).

Discussion Character

  • Exploratory, Assumption checking, Problem interpretation

Approaches and Questions Raised

  • The original poster attempts to solve for x3 and x4 using the constraints and substitutes them into the objective function. Some participants question the notation used for x4 and discuss the implications of solving for x4 versus x4^2. There is also a suggestion that the problem may involve maximizing the function instead of minimizing it.

Discussion Status

The discussion is ongoing, with participants providing feedback on the original poster's approach and clarifying terminology. There is no explicit consensus on the interpretation of the problem, but some guidance has been offered regarding the notation and the nature of the optimization.

Contextual Notes

Participants note the use of acronyms like NLO and DFP, with some expressing confusion about their meanings. The original poster clarifies that the goal is to reduce the problem rather than maximize it, indicating a specific focus on the reduction process.

ver_mathstats
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Homework Statement
We are required to reduce an unconstrained optimization problem. Problem is written below.
Relevant Equations
reduce to an unconstrained optimization problem
We are given the problem min x3-x42 such that (1): x12 + x3 = 2 and (2): (x2-x4)(x2+x4)=1.

What I did was solve for x3 in (1) and then solve for x4 in (2). I substituted those equations into min x3-x42 and I obtain the solution: 2-x12-x22+1, would this be the correct approach to this problem?

Thank you!
 
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You wrote ##x_{4^2}## in a couple of places, is that supposed to be ##x_4^2##?
I think you solved the problem just fine, but I would note literally solving for. ##x_4## requires writing down a ##\pm## which you have to carefully observe goes away when you square it, whereas solving for ##x_4^2## and substituting that does not.

Are you supposed to solve this? It's kind of weird, I think maybe they wanted you to maximize the function?
 
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Office_Shredder said:
You wrote ##x_{4^2}## in a couple of places, is that supposed to be ##x_4^2##?
I think you solved the problem just fine, but I would note literally solving for. ##x_4## requires writing down a ##\pm## which you have to carefully observe goes away when you square it, whereas solving for ##x_4^2## and substituting that does not.

Are you supposed to solve this? It's kind of weird, I think maybe they wanted you to maximize the function?
Yes I meant it to be the second one my apologies. No no, I just needed to reduce it and was making sure I was on the right track, we do not have to maximize it, the next part is to do DFP on the problem.
 
@ver_mathstats, please don't write acronyms without explaining what they mean. For example, I guess that NLO stands for nonlinear optimization, but I have no idea what DFP stands for.
 
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Mark44 said:
@ver_mathstats, please don't write acronyms without explaining what they mean. For example, I guess that NLO stands for nonlinear optimization, but I have no idea what DFP stands for.
Sorry I'm just so used to that, it's the David Fletcher Powell method.
 
ver_mathstats said:
Sorry I'm just so used to that, it's the David Fletcher Powell method.
I'd be surprised if anyone at this site has heard of this guy, let alone would know what DFP stands for.
 

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