Given an NLO reduce it to unconstrained optimization problem

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SUMMARY

The discussion focuses on reducing a nonlinear optimization (NLO) problem to an unconstrained optimization problem. The user successfully solved for variables x3 and x4 using the constraints x1^2 + x3 = 2 and (x2 - x4)(x2 + x4) = 1, leading to the expression 2 - x1^2 - x2^2 + 1. The conversation highlights the importance of correctly interpreting variable notation, specifically distinguishing between x4 and x4^2, and clarifies that the next step involves applying the David Fletcher Powell (DFP) method for optimization.

PREREQUISITES
  • Understanding of nonlinear optimization (NLO)
  • Familiarity with the David Fletcher Powell (DFP) method
  • Knowledge of substitution methods in optimization problems
  • Ability to manipulate algebraic expressions and constraints
NEXT STEPS
  • Study the David Fletcher Powell (DFP) method for optimization
  • Learn about constraints in nonlinear optimization problems
  • Explore techniques for maximizing functions under constraints
  • Investigate the implications of variable notation in mathematical expressions
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Mathematicians, optimization specialists, and students studying nonlinear optimization techniques will benefit from this discussion.

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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