[R] [Fwd: Re: optimization subject to constraints]

[Gildas Mazo]

Thanks Ravi.

Gildas


Ravi Varadhan a écrit :
> I think the problem is because the the Hessian of the augmented Lagrangian iis singular at c(0,0). 
>
> Try this:
>
> require(alabama)
>
> heq <- function(x) {
> x[1]^2+x[2]^2 - 1
> }
>
>   
>>  constrOptim.nl(par=c(0,0), fn=f, heq=heq, control.outer=list(trace=FALSE))
>>     
> $par
> [1] -0.7071067 -0.7071067
>
> $value
> [1] -1.414213
>
> $iterations
> [1] 10
>
> $lambda
> [1] -0.7068717
>
> $penalty
> [1] -6.496021e-08
>
> $counts
> function gradient 
>      100       30 
>
>
> Ravi.
>
> ____________________________________________________________________
>
> Ravi Varadhan, Ph.D.
> Assistant Professor,
> Division of Geriatric Medicine and Gerontology
> School of Medicine
> Johns Hopkins University
>
> Ph. (410) 502-2619
> email: rvaradhan at jhmi.edu
>
>
> ----- Original Message -----
> From: Gildas Mazo <gildas.mazo at curie.fr>
> Date: Tuesday, August 10, 2010 10:11 am
> Subject: [R] [Fwd: Re:  optimization subject to constraints]
> To: r-help at r-project.org
>
>
>   
>> ----- Original Message -----
>>     
>
>   
>>  From Gildas Mazo <gildas.mazo at curie.fr>
>>     
>
>   
>>  Date Tue, 10 Aug 2010 15:49:19 +0200
>>     
>
>   
>>  To Matthias Gondan <matthias-gondan at gmx.de>
>>     
>  Subject Re: [R] optimization subject to constraints
>   
>> Danke schön Matthias.
>>  
>>   I had naively started with x0 = c(0,0) and I got a "Redundant
>>  constraints were found" error. What's the problem with (0,0) ?
>>  
>>  
>>  
>>  
>>  
>>  
>>  
>>  Matthias Gondan a écrit :
>>  >  try this (package Rsolnp)
>>  >
>>  > library(Rsolnp)
>>  >
>>  > g<- function(x)
>>  > {
>>  >   return(x[1]^2+x[2]^2)
>>  > } # constraint
>>  >
>>  > f<- function(x)
>>  > {
>>  >   return(x[1]+x[2])
>>  > } # objective function
>>  >
>>  > x0 = c(1, 1)
>>  >
>>  > solnp(x0, fun=f, eqfun=g, eqB=c(1))
>>  >
>>  >
>>  >
>>  > Am 10.08.2010 14:59, schrieb Gildas Mazo:
>>  >> Thanks, but I still cannot get to solve my problem: consider this 
>> simple
>>  >> example:
>>  >>
>>  >> ########
>>  >>
>>  >> f<- function(x){
>>  >>    return(x[1]+x[2])
>>  >> } # objective function
>>  >>
>>  >> g<- function(x){
>>  >>    return(x[1]^2+x[2]^2)
>>  >> } # constraint
>>  >>
>>  >> #########
>>  >>
>>  >> I wanna Maximize f(x) subject to g(x) = 1. By hand the solution is
>>  >> (1/sqrt(2), 1/sqrt(2), sqrt(2)). This is to maximizing a linear function
>>  >> subject to a nonlinear equality constraint.  I didn't find any suitable
>>  >> function in the packages I went through.
>>  >>
>>  >> Thanks in advance,
>>  >>
>>  >> Gildas
>>  >>
>>  >>
>>  >>
>>  >>
>>  >>
>>  >> Spencer Graves a écrit :
>>  >>>         To find every help page containing the term "constrained
>>  >>> optimization", you can try the following:
>>  >>>
>>  >>>
>>  >>> library(sos)
>>  >>> co<- findFn('constrained optimization')
>>  >>>
>>  >>>
>>  >>>        "Printing" this "co" object opens a table in a web browser 
>> with
>>  >>> all matches sorted first by the package with the most matches and 
>> with
>>  >>> hot links to the documentation page.
>>  >>>
>>  >>>
>>  >>> writeFindFn2xls(co)
>>  >>>
>>  >>>
>>  >>>        This writes an excel file, with the browser table as the second
>>  >>> tab and the first being a summary of the packages.  This summary 
>> table
>>  >>> can be made more complete and useful using the "installPackages"
>>  >>> function, as noted in the "sos" vignette.
>>  >>>
>>  >>>
>>  >>>        A shameless plug from the lead author of the  "sos" package.
>>  >>>        Spencer Graves
>>  >>>
>>  >>>
>>  >>> On 8/9/2010 10:01 AM, Ravi Varadhan wrote:
>>  >>>> constrOptim can only handle linear inequality constraints.  It cannot
>>  >>>> handle
>>  >>>> equality (linear or nonlinear) as well as nonlinear inequality
>>  >>>> constraints.
>>  >>>>
>>  >>>> Ravi.
>>  >>>>
>>  >>>> -----Original Message-----
>>  >>>> From: r-help-bounces at r-project.org
>>  >>>> [ On
>>  >>>> Behalf Of Dwayne Blind
>>  >>>> Sent: Monday, August 09, 2010 12:56 PM
>>  >>>> To: Gildas Mazo
>>  >>>> Cc: r-help at r-project.org
>>  >>>> Subject: Re: [R] optimization subject to constraints
>>  >>>>
>>  >>>> Hi !
>>  >>>>
>>  >>>> Why not constrOptim ?
>>  >>>>
>>  >>>> Dwayne
>>  >>>>
>>  >>>> 2010/8/9 Gildas Mazo<gildas.mazo at curie.fr>
>>  >>>>
>>  >>>>> Dear R users,
>>  >>>>>
>>  >>>>> I'm looking for tools to perform optimization subject to constraints,
>>  >>>>> both linear and non-linear. I don't mind which algorithm may be
>>  >>>>> used, my
>>  >>>>> primary aim is to get something general and easy-to-use to study
>>  >>>>> simples
>>  >>>>> examples.
>>  >>>>>
>>  >>>>> Thanks for helping,
>>  >>>>>
>>  >>>>> Gildas
>>  >>>>>
>>  >>>>> ______________________________________________
>>  >>>>> R-help at r-project.org mailing list
>>  >>>>> 
>>  >>>>> PLEASE do read the posting guide
>>  >>>>>
>>  >>>> 
>>  >>>>
>>  >>>>
>>  >>>> -guide.html>
>>  >>>>> and provide commented, minimal, self-contained, reproducible code.
>>  >>>>>
>>  >>>>      [[alternative HTML version deleted]]
>>  >>>>
>>  >>>> ______________________________________________
>>  >>>> R-help at r-project.org mailing list
>>  >>>> 
>>  >>>> PLEASE do read the posting guide
>>  >>>> 
>>  >>>> and provide commented, minimal, self-contained, reproducible code.
>>  >>>>
>>  >>>> ______________________________________________
>>  >>>> R-help at r-project.org mailing list
>>  >>>> 
>>  >>>> PLEASE do read the posting guide
>>  >>>> 
>>  >>>> and provide commented, minimal, self-contained, reproducible code.
>>  >>
>>  >
>>  > ______________________________________________
>>  > R-help at r-project.org mailing list
>>  > 
>>  > PLEASE do read the posting guide
>>  > 
>>  > and provide commented, minimal, self-contained, reproducible code.
>>  >
>>  >
>>  
>>   
>> ______________________________________________
>>  R-help at r-project.org mailing list
>>  
>>  PLEASE do read the posting guide 
>>  and provide commented, minimal, self-contained, reproducible code.
>>     
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
>