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Thread Subject:
Minimisation problem

Subject: Minimisation problem

From: aaron brocq

Date: 24 Apr, 2009 13:46:36

Message: 1 of 2

I have the following functionf=x^(1/2) which when I minimise using fminunc, BFGS, DFP and Steepest Descent the following output is given for each method;

>> y=fminunc(@Fun2a,3, options);
Warning: Gradient must be provided for trust-region method;
  using line-search method instead.
> In fminunc at 281
                                                        First-order
 Iteration Func-count f(x) Step-size optimality
     0 2 1.73205 0.289
     1 8 2.95375e-016 91 0.104
Line search cannot find an acceptable point along the current
 search direction.
Does this mean it cannot find an optimum for the function?

This post is tied in with my other post,appreciate any help.
 Aaron

Subject: Minimisation problem

From: John D'Errico

Date: 24 Apr, 2009 14:00:03

Message: 2 of 2

aaron brocq <arun.september@gmail.com> wrote in message <22231055.5054.1240580827422.JavaMail.jakarta@nitrogen.mathforum.org>...
> I have the following functionf=x^(1/2) which when I minimise using fminunc, BFGS, DFP and Steepest Descent the following output is given for each method;
>
> >> y=fminunc(@Fun2a,3, options);
> Warning: Gradient must be provided for trust-region method;
> using line-search method instead.
> > In fminunc at 281
> First-order
> Iteration Func-count f(x) Step-size optimality
> 0 2 1.73205 0.289
> 1 8 2.95375e-016 91 0.104
> Line search cannot find an acceptable point along the current
> search direction.
> Does this mean it cannot find an optimum for the function?
>
> This post is tied in with my other post,appreciate any help.
> Aaron

You are trying to minimize sqrt(x), using an UNCONSTRAINED
optimizer? What does it mean to ask for the minimum of
sqrt(x) over the entire real line?

What do you expect it to do when fminunc tries to search
below zero? Fminunc assumes a REAL valued function.

John

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