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Paul Smith

2007-Jul-03 20:10 UTC

[R] Fine tunning rgenoud

Dear All,

I am trying to solve the following maximization problem, but I cannot
have rgenoud giving me a reliable solution.

Any ideas?

Thanks in advance,

Paul

----------------------------
library(rgenoud)

v <- 0.90
O1 <- 10
O2 <- 20
O0 <- v*O1+(1-v)*O2

myfunc <- function(x) {
  U0 <- x[1]
  U1 <- x[2]
  U2 <- x[3]
  q0 <- x[4]
  q1 <- x[5]
  q2 <- x[6]
  p <- x[7]

  if (U0 < 0)
    return(-1e+200)
  else if (U1 < 0)
    return(-1e+200)
  else if (U2 < 0)
    return(-1e+200)
  else if ((U0-(U1+(O1-O0)*q1)) < 0)
    return(-1e+200)
  else if ((U0-(U2+(O2-O0)*q2)) < 0)
    return(-1e+200)
  else if ((U1-(U0+(O0-O1)*q0)) < 0)
    return(-1e+200)
  else if ((U1-(U2+(O2-O1)*q2)) < 0)
    return(-1e+200)
  else if((U2-(U0+(O0-O2)*q0)) < 0)
    return(-1e+200)
  else if((U2-(U1+(O1-O2)*q1)) < 0)
    return(-1e+200)
  else if(p < 0)
    return(-1e+200)
  else if(p > 1)
    return(-1e+200)
  else if(q0 < 0)
    return(-1e+200)
  else if(q1 < 0)
    return(-1e+200)
  else if(q2 < 0)
    return(-1e+200)
  else
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2)-(O2*q2+U2))))

}
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.generations=150,max.generations=300,boundary.enforcement=2)

Ravi Varadhan

2007-Jul-03 20:50 UTC

head link

[R] Fine tunning rgenoud

Paul,

You had indicated in your previous email that you are having trouble finding
a feasible starting value for constrOptim().  So, you basically need to
solve a system of linear inequalities to obtain a starting point.  Have you
considered using linear programming? Either simplex() in the "boot"
package
or solveLP() in "linprog" would work.  It seems to me that you could
use any
linear objective function in solveLP to obtain a feasible starting point.
This is not the most efficient solution, but it might be worth a try. 

I am aware of other methods for generating n-tuples that satisfy linear
inequality constraints, but AFAIK those are not available in R.

Best,
Ravi.


----------------------------------------------------------------------------
-------

Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology 

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan at jhmi.edu

Webpage:  http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html

 

----------------------------------------------------------------------------
--------

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
Sent: Tuesday, July 03, 2007 4:10 PM
To: R-help
Subject: [R] Fine tunning rgenoud

Dear All,

I am trying to solve the following maximization problem, but I cannot
have rgenoud giving me a reliable solution.

Any ideas?

Thanks in advance,

Paul

----------------------------
library(rgenoud)

v <- 0.90
O1 <- 10
O2 <- 20
O0 <- v*O1+(1-v)*O2

myfunc <- function(x) {
  U0 <- x[1]
  U1 <- x[2]
  U2 <- x[3]
  q0 <- x[4]
  q1 <- x[5]
  q2 <- x[6]
  p <- x[7]

  if (U0 < 0)
    return(-1e+200)
  else if (U1 < 0)
    return(-1e+200)
  else if (U2 < 0)
    return(-1e+200)
  else if ((U0-(U1+(O1-O0)*q1)) < 0)
    return(-1e+200)
  else if ((U0-(U2+(O2-O0)*q2)) < 0)
    return(-1e+200)
  else if ((U1-(U0+(O0-O1)*q0)) < 0)
    return(-1e+200)
  else if ((U1-(U2+(O2-O1)*q2)) < 0)
    return(-1e+200)
  else if((U2-(U0+(O0-O2)*q0)) < 0)
    return(-1e+200)
  else if((U2-(U1+(O1-O2)*q1)) < 0)
    return(-1e+200)
  else if(p < 0)
    return(-1e+200)
  else if(p > 1)
    return(-1e+200)
  else if(q0 < 0)
    return(-1e+200)
  else if(q1 < 0)
    return(-1e+200)
  else if(q2 < 0)
    return(-1e+200)
  else
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
)-(O2*q2+U2))))

}
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
rations=150,max.generations=300,boundary.enforcement=2)

______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Paul Smith

2007-Jul-03 21:09 UTC

head link

[R] Fine tunning rgenoud

On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:> You had indicated in your previous email that you are having trouble
finding
> a feasible starting value for constrOptim().  So, you basically need to
> solve a system of linear inequalities to obtain a starting point.  Have you
> considered using linear programming? Either simplex() in the
"boot" package
> or solveLP() in "linprog" would work.  It seems to me that you
could use any
> linear objective function in solveLP to obtain a feasible starting point.
> This is not the most efficient solution, but it might be worth a try.
>
> I am aware of other methods for generating n-tuples that satisfy linear
> inequality constraints, but AFAIK those are not available in R.
Thanks, Ravi. I had already conceived the solution that you suggest,
actually using "lpSolve". I am able to get a solution for my problem
with constrOptim, but I am not enough confident that the solution is
right. That is why I am trying to get a solution with rgenoud, but
unsuccessfully until now.

Paul


> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> Sent: Tuesday, July 03, 2007 4:10 PM
> To: R-help
> Subject: [R] Fine tunning rgenoud
>
> Dear All,
>
> I am trying to solve the following maximization problem, but I cannot
> have rgenoud giving me a reliable solution.
>
> Any ideas?
>
> Thanks in advance,
>
> Paul
>
> ----------------------------
> library(rgenoud)
>
> v <- 0.90
> O1 <- 10
> O2 <- 20
> O0 <- v*O1+(1-v)*O2
>
> myfunc <- function(x) {
>   U0 <- x[1]
>   U1 <- x[2]
>   U2 <- x[3]
>   q0 <- x[4]
>   q1 <- x[5]
>   q2 <- x[6]
>   p <- x[7]
>
>   if (U0 < 0)
>     return(-1e+200)
>   else if (U1 < 0)
>     return(-1e+200)
>   else if (U2 < 0)
>     return(-1e+200)
>   else if ((U0-(U1+(O1-O0)*q1)) < 0)
>     return(-1e+200)
>   else if ((U0-(U2+(O2-O0)*q2)) < 0)
>     return(-1e+200)
>   else if ((U1-(U0+(O0-O1)*q0)) < 0)
>     return(-1e+200)
>   else if ((U1-(U2+(O2-O1)*q2)) < 0)
>     return(-1e+200)
>   else if((U2-(U0+(O0-O2)*q0)) < 0)
>     return(-1e+200)
>   else if((U2-(U1+(O1-O2)*q1)) < 0)
>     return(-1e+200)
>   else if(p < 0)
>     return(-1e+200)
>   else if(p > 1)
>     return(-1e+200)
>   else if(q0 < 0)
>     return(-1e+200)
>   else if(q1 < 0)
>     return(-1e+200)
>   else if(q2 < 0)
>     return(-1e+200)
>   else
>
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> )-(O2*q2+U2))))
>
> }
>
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> rations=150,max.generations=300,boundary.enforcement=2)
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

Ravi Varadhan

2007-Jul-03 23:02 UTC

head link

[R] Fine tunning rgenoud

Paul,

It should be easy enough to check that your solution is valid (i.e. a local
minimum):  first, check to see if the solution satisfies all the
constraints; secondly, check to see if it is an interior point (i.e. none of
the constraints become equality); and finally, if the solution is an
interior point, check to see whether the gradient there is close to zero.
Note that if the solution is one of the vertices of the polyhedron, then the
gradient may not be zero.

Ravi.

----------------------------------------------------------------------------
-------

Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology 

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan at jhmi.edu

Webpage:  http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html

 

----------------------------------------------------------------------------
--------


-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
Sent: Tuesday, July 03, 2007 5:10 PM
To: R-help
Subject: Re: [R] Fine tunning rgenoud

On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:> You had indicated in your previous email that you are having trouble
finding> a feasible starting value for constrOptim().  So, you basically need to
> solve a system of linear inequalities to obtain a starting point.  Have
you> considered using linear programming? Either simplex() in the
"boot"
package> or solveLP() in "linprog" would work.  It seems to me that you
could use
any> linear objective function in solveLP to obtain a feasible starting point.
> This is not the most efficient solution, but it might be worth a try.
>
> I am aware of other methods for generating n-tuples that satisfy linear
> inequality constraints, but AFAIK those are not available in R.
Thanks, Ravi. I had already conceived the solution that you suggest,
actually using "lpSolve". I am able to get a solution for my problem
with constrOptim, but I am not enough confident that the solution is
right. That is why I am trying to get a solution with rgenoud, but
unsuccessfully until now.

Paul


> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> Sent: Tuesday, July 03, 2007 4:10 PM
> To: R-help
> Subject: [R] Fine tunning rgenoud
>
> Dear All,
>
> I am trying to solve the following maximization problem, but I cannot
> have rgenoud giving me a reliable solution.
>
> Any ideas?
>
> Thanks in advance,
>
> Paul
>
> ----------------------------
> library(rgenoud)
>
> v <- 0.90
> O1 <- 10
> O2 <- 20
> O0 <- v*O1+(1-v)*O2
>
> myfunc <- function(x) {
>   U0 <- x[1]
>   U1 <- x[2]
>   U2 <- x[3]
>   q0 <- x[4]
>   q1 <- x[5]
>   q2 <- x[6]
>   p <- x[7]
>
>   if (U0 < 0)
>     return(-1e+200)
>   else if (U1 < 0)
>     return(-1e+200)
>   else if (U2 < 0)
>     return(-1e+200)
>   else if ((U0-(U1+(O1-O0)*q1)) < 0)
>     return(-1e+200)
>   else if ((U0-(U2+(O2-O0)*q2)) < 0)
>     return(-1e+200)
>   else if ((U1-(U0+(O0-O1)*q0)) < 0)
>     return(-1e+200)
>   else if ((U1-(U2+(O2-O1)*q2)) < 0)
>     return(-1e+200)
>   else if((U2-(U0+(O0-O2)*q0)) < 0)
>     return(-1e+200)
>   else if((U2-(U1+(O1-O2)*q1)) < 0)
>     return(-1e+200)
>   else if(p < 0)
>     return(-1e+200)
>   else if(p > 1)
>     return(-1e+200)
>   else if(q0 < 0)
>     return(-1e+200)
>   else if(q1 < 0)
>     return(-1e+200)
>   else if(q2 < 0)
>     return(-1e+200)
>   else
>
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2> )-(O2*q2+U2))))
>
> }
>
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene> rations=150,max.generations=300,boundary.enforcement=2)
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
>
______________________________________________
R-help at stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Paul Smith

2007-Jul-03 23:13 UTC

head link

[R] Fine tunning rgenoud

On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:> It should be easy enough to check that your solution is valid (i.e. a local
> minimum):  first, check to see if the solution satisfies all the
> constraints; secondly, check to see if it is an interior point (i.e. none
of
> the constraints become equality); and finally, if the solution is an
> interior point, check to see whether the gradient there is close to zero.
> Note that if the solution is one of the vertices of the polyhedron, then
the
> gradient may not be zero.
That is a very good idea, Ravi! Thanks!

Paul


> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> Sent: Tuesday, July 03, 2007 5:10 PM
> To: R-help
> Subject: Re: [R] Fine tunning rgenoud
>
> On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
> > You had indicated in your previous email that you are having trouble
> finding
> > a feasible starting value for constrOptim().  So, you basically need
to
> > solve a system of linear inequalities to obtain a starting point. 
Have
> you
> > considered using linear programming? Either simplex() in the
"boot"
> package
> > or solveLP() in "linprog" would work.  It seems to me that
you could use
> any
> > linear objective function in solveLP to obtain a feasible starting
point.
> > This is not the most efficient solution, but it might be worth a try.
> >
> > I am aware of other methods for generating n-tuples that satisfy
linear
> > inequality constraints, but AFAIK those are not available in R.
>
> Thanks, Ravi. I had already conceived the solution that you suggest,
> actually using "lpSolve". I am able to get a solution for my
problem
> with constrOptim, but I am not enough confident that the solution is
> right. That is why I am trying to get a solution with rgenoud, but
> unsuccessfully until now.
>
> Paul
>
>
>
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> > Sent: Tuesday, July 03, 2007 4:10 PM
> > To: R-help
> > Subject: [R] Fine tunning rgenoud
> >
> > Dear All,
> >
> > I am trying to solve the following maximization problem, but I cannot
> > have rgenoud giving me a reliable solution.
> >
> > Any ideas?
> >
> > Thanks in advance,
> >
> > Paul
> >
> > ----------------------------
> > library(rgenoud)
> >
> > v <- 0.90
> > O1 <- 10
> > O2 <- 20
> > O0 <- v*O1+(1-v)*O2
> >
> > myfunc <- function(x) {
> >   U0 <- x[1]
> >   U1 <- x[2]
> >   U2 <- x[3]
> >   q0 <- x[4]
> >   q1 <- x[5]
> >   q2 <- x[6]
> >   p <- x[7]
> >
> >   if (U0 < 0)
> >     return(-1e+200)
> >   else if (U1 < 0)
> >     return(-1e+200)
> >   else if (U2 < 0)
> >     return(-1e+200)
> >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
> >     return(-1e+200)
> >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
> >     return(-1e+200)
> >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
> >     return(-1e+200)
> >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
> >     return(-1e+200)
> >   else if((U2-(U0+(O0-O2)*q0)) < 0)
> >     return(-1e+200)
> >   else if((U2-(U1+(O1-O2)*q1)) < 0)
> >     return(-1e+200)
> >   else if(p < 0)
> >     return(-1e+200)
> >   else if(p > 1)
> >     return(-1e+200)
> >   else if(q0 < 0)
> >     return(-1e+200)
> >   else if(q1 < 0)
> >     return(-1e+200)
> >   else if(q2 < 0)
> >     return(-1e+200)
> >   else
> >
>
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> > )-(O2*q2+U2))))
> >
> > }
> >
>
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> > rations=150,max.generations=300,boundary.enforcement=2)
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

Paul Smith

2007-Jul-03 23:31 UTC

head link

[R] Fine tunning rgenoud

On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:> It should be easy enough to check that your solution is valid (i.e. a local
> minimum):  first, check to see if the solution satisfies all the
> constraints; secondly, check to see if it is an interior point (i.e. none
of
> the constraints become equality); and finally, if the solution is an
> interior point, check to see whether the gradient there is close to zero.
> Note that if the solution is one of the vertices of the polyhedron, then
the
> gradient may not be zero.
I am having bad luck: all constraints are satisfied, but the solution
given by constrOptim is not interior; the gradient is not equal to
zero.

Paul

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> Sent: Tuesday, July 03, 2007 5:10 PM
> To: R-help
> Subject: Re: [R] Fine tunning rgenoud
>
> On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
> > You had indicated in your previous email that you are having trouble
> finding
> > a feasible starting value for constrOptim().  So, you basically need
to
> > solve a system of linear inequalities to obtain a starting point. 
Have
> you
> > considered using linear programming? Either simplex() in the
"boot"
> package
> > or solveLP() in "linprog" would work.  It seems to me that
you could use
> any
> > linear objective function in solveLP to obtain a feasible starting
point.
> > This is not the most efficient solution, but it might be worth a try.
> >
> > I am aware of other methods for generating n-tuples that satisfy
linear
> > inequality constraints, but AFAIK those are not available in R.
>
> Thanks, Ravi. I had already conceived the solution that you suggest,
> actually using "lpSolve". I am able to get a solution for my
problem
> with constrOptim, but I am not enough confident that the solution is
> right. That is why I am trying to get a solution with rgenoud, but
> unsuccessfully until now.
>
> Paul
>
>
>
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Paul Smith
> > Sent: Tuesday, July 03, 2007 4:10 PM
> > To: R-help
> > Subject: [R] Fine tunning rgenoud
> >
> > Dear All,
> >
> > I am trying to solve the following maximization problem, but I cannot
> > have rgenoud giving me a reliable solution.
> >
> > Any ideas?
> >
> > Thanks in advance,
> >
> > Paul
> >
> > ----------------------------
> > library(rgenoud)
> >
> > v <- 0.90
> > O1 <- 10
> > O2 <- 20
> > O0 <- v*O1+(1-v)*O2
> >
> > myfunc <- function(x) {
> >   U0 <- x[1]
> >   U1 <- x[2]
> >   U2 <- x[3]
> >   q0 <- x[4]
> >   q1 <- x[5]
> >   q2 <- x[6]
> >   p <- x[7]
> >
> >   if (U0 < 0)
> >     return(-1e+200)
> >   else if (U1 < 0)
> >     return(-1e+200)
> >   else if (U2 < 0)
> >     return(-1e+200)
> >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
> >     return(-1e+200)
> >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
> >     return(-1e+200)
> >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
> >     return(-1e+200)
> >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
> >     return(-1e+200)
> >   else if((U2-(U0+(O0-O2)*q0)) < 0)
> >     return(-1e+200)
> >   else if((U2-(U1+(O1-O2)*q1)) < 0)
> >     return(-1e+200)
> >   else if(p < 0)
> >     return(-1e+200)
> >   else if(p > 1)
> >     return(-1e+200)
> >   else if(q0 < 0)
> >     return(-1e+200)
> >   else if(q1 < 0)
> >     return(-1e+200)
> >   else if(q2 < 0)
> >     return(-1e+200)
> >   else
> >
>
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> > )-(O2*q2+U2))))
> >
> > }
> >
>
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> > rations=150,max.generations=300,boundary.enforcement=2)
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

RAVI VARADHAN

2007-Jul-04 04:30 UTC

head link

[R] Fine tunning rgenoud

Paul,

Here is another approach: I wrote an R function that would generate interior
points as starting values for constrOptim.  This might work better than the LP
approach, since the LP approach gives you a starting value that is on the
boundary of the feasible region, i.e a vertex of the polyhedron, whereas this
new approach gives you points on the interior.  You can generate as many points
as you wish, but the approach is brute-force and is very inefficient - it takes
on the order of a 1000 tries to find one feasible point.

Hope this helps,
Ravi. 

----- Original Message -----
From: Paul Smith <phhs80 at gmail.com>
Date: Tuesday, July 3, 2007 7:32 pm
Subject: Re: [R] Fine tunning rgenoud
To: R-help <r-help at stat.math.ethz.ch>

> On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
>  > It should be easy enough to check that your solution is valid (i.e. 
> a local
>  > minimum):  first, check to see if the solution satisfies all the
>  > constraints; secondly, check to see if it is an interior point 
> (i.e. none of
>  > the constraints become equality); and finally, if the solution is an
>  > interior point, check to see whether the gradient there is close to 
> zero.
>  > Note that if the solution is one of the vertices of the polyhedron, 
> then the
>  > gradient may not be zero.
>  
>  I am having bad luck: all constraints are satisfied, but the solution
>  given by constrOptim is not interior; the gradient is not equal to
>  zero.
>  
>  Paul
>  
>  
>  > -----Original Message-----
>  > From: r-help-bounces at stat.math.ethz.ch
>  > [ On Behalf Of Paul Smith
>  > Sent: Tuesday, July 03, 2007 5:10 PM
>  > To: R-help
>  > Subject: Re: [R] Fine tunning rgenoud
>  >
>  > On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
>  > > You had indicated in your previous email that you are having
trouble
>  > finding
>  > > a feasible starting value for constrOptim().  So, you basically 
> need to
>  > > solve a system of linear inequalities to obtain a starting
point.
>  Have
>  > you
>  > > considered using linear programming? Either simplex() in the
"boot"
>  > package
>  > > or solveLP() in "linprog" would work.  It seems to me
that you
> could use
>  > any
>  > > linear objective function in solveLP to obtain a feasible 
> starting point.
>  > > This is not the most efficient solution, but it might be worth a
> try.
>  > >
>  > > I am aware of other methods for generating n-tuples that satisfy
> linear
>  > > inequality constraints, but AFAIK those are not available in R.
>  >
>  > Thanks, Ravi. I had already conceived the solution that you suggest,
>  > actually using "lpSolve". I am able to get a solution for
my problem
>  > with constrOptim, but I am not enough confident that the solution is
>  > right. That is why I am trying to get a solution with rgenoud, but
>  > unsuccessfully until now.
>  >
>  > Paul
>  >
>  >
>  >
>  > > -----Original Message-----
>  > > From: r-help-bounces at stat.math.ethz.ch
>  > > [ On Behalf Of Paul Smith
>  > > Sent: Tuesday, July 03, 2007 4:10 PM
>  > > To: R-help
>  > > Subject: [R] Fine tunning rgenoud
>  > >
>  > > Dear All,
>  > >
>  > > I am trying to solve the following maximization problem, but I
cannot
>  > > have rgenoud giving me a reliable solution.
>  > >
>  > > Any ideas?
>  > >
>  > > Thanks in advance,
>  > >
>  > > Paul
>  > >
>  > > ----------------------------
>  > > library(rgenoud)
>  > >
>  > > v <- 0.90
>  > > O1 <- 10
>  > > O2 <- 20
>  > > O0 <- v*O1+(1-v)*O2
>  > >
>  > > myfunc <- function(x) {
>  > >   U0 <- x[1]
>  > >   U1 <- x[2]
>  > >   U2 <- x[3]
>  > >   q0 <- x[4]
>  > >   q1 <- x[5]
>  > >   q2 <- x[6]
>  > >   p <- x[7]
>  > >
>  > >   if (U0 < 0)
>  > >     return(-1e+200)
>  > >   else if (U1 < 0)
>  > >     return(-1e+200)
>  > >   else if (U2 < 0)
>  > >     return(-1e+200)
>  > >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
>  > >     return(-1e+200)
>  > >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
>  > >     return(-1e+200)
>  > >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
>  > >     return(-1e+200)
>  > >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
>  > >     return(-1e+200)
>  > >   else if((U2-(U0+(O0-O2)*q0)) < 0)
>  > >     return(-1e+200)
>  > >   else if((U2-(U1+(O1-O2)*q1)) < 0)
>  > >     return(-1e+200)
>  > >   else if(p < 0)
>  > >     return(-1e+200)
>  > >   else if(p > 1)
>  > >     return(-1e+200)
>  > >   else if(q0 < 0)
>  > >     return(-1e+200)
>  > >   else if(q1 < 0)
>  > >     return(-1e+200)
>  > >   else if(q2 < 0)
>  > >     return(-1e+200)
>  > >   else
>  > >
>  >
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
>  > > )-(O2*q2+U2))))
>  > >
>  > > }
>  > >
>  >
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
>  > > rations=150,max.generations=300,boundary.enforcement=2)
>  > >
>  > > ______________________________________________
>  > > R-help at stat.math.ethz.ch mailing list
>  > > 
>  > > PLEASE do read the posting guide
>  > 
>  > > and provide commented, minimal, self-contained, reproducible
code.
>  > >
>  >
>  > ______________________________________________
>  > R-help at stat.math.ethz.ch mailing list
>  > 
>  > PLEASE do read the posting guide 
>  > and provide commented, minimal, self-contained, reproducible code.
>  >
>  
>  ______________________________________________
>  R-help at stat.math.ethz.ch mailing list
>  
>  PLEASE do read the posting guide 
>  and provide commented, minimal, self-contained, reproducible code. -------------- next part --------------
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Patrick Burns

2007-Jul-04 08:20 UTC

head link

[R] Fine tunning rgenoud

I think fine tuning the function might be in order.

The function has just a single penalty for not meeting
the constraints no matter how close it is to meeting
them.  A better approach is to have a penalty that
depends on the amount by which all of the constraints
are breached.


Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")


Paul Smith wrote:
>Dear All,
>
>I am trying to solve the following maximization problem, but I cannot
>have rgenoud giving me a reliable solution.
>
>Any ideas?
>
>Thanks in advance,
>
>Paul
>
>----------------------------
>library(rgenoud)
>
>v <- 0.90
>O1 <- 10
>O2 <- 20
>O0 <- v*O1+(1-v)*O2
>
>myfunc <- function(x) {
>  U0 <- x[1]
>  U1 <- x[2]
>  U2 <- x[3]
>  q0 <- x[4]
>  q1 <- x[5]
>  q2 <- x[6]
>  p <- x[7]
>
>  if (U0 < 0)
>    return(-1e+200)
>  else if (U1 < 0)
>    return(-1e+200)
>  else if (U2 < 0)
>    return(-1e+200)
>  else if ((U0-(U1+(O1-O0)*q1)) < 0)
>    return(-1e+200)
>  else if ((U0-(U2+(O2-O0)*q2)) < 0)
>    return(-1e+200)
>  else if ((U1-(U0+(O0-O1)*q0)) < 0)
>    return(-1e+200)
>  else if ((U1-(U2+(O2-O1)*q2)) < 0)
>    return(-1e+200)
>  else if((U2-(U0+(O0-O2)*q0)) < 0)
>    return(-1e+200)
>  else if((U2-(U1+(O1-O2)*q1)) < 0)
>    return(-1e+200)
>  else if(p < 0)
>    return(-1e+200)
>  else if(p > 1)
>    return(-1e+200)
>  else if(q0 < 0)
>    return(-1e+200)
>  else if(q1 < 0)
>    return(-1e+200)
>  else if(q2 < 0)
>    return(-1e+200)
>  else
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2)-(O2*q2+U2))))
>
>}
>genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.generations=150,max.generations=300,boundary.enforcement=2)
>
>______________________________________________
>R-help at stat.math.ethz.ch mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
>
>
>  
>

Paul Smith

2007-Jul-04 09:59 UTC

head link

[R] Fine tunning rgenoud

On 7/4/07, RAVI VARADHAN <rvaradhan at jhmi.edu>
wrote:> Here is another approach: I wrote an R function that would generate
interior points as starting values for constrOptim.  This might work better than
the LP approach, since the LP approach gives you a starting value that is on the
boundary of the feasible region, i.e a vertex of the polyhedron, whereas this
new approach gives you points on the interior.  You can generate as many points
as you wish, but the approach is brute-force and is very inefficient - it takes
on the order of a 1000 tries to find one feasible point.
Thanks again, Ravi. Actually, the LP approach also works here. Let
g(X) >= k be the constraints. Then, by solving a LP problem with the
constraints

g(X) >= (k+0.2)

returns an interior starting value for constrOptim. I am aware that
the new set of constraints may correspond to an impossible linear
system, but it works in many cases.

Paul
> ----- Original Message -----
> From: Paul Smith <phhs80 at gmail.com>
> Date: Tuesday, July 3, 2007 7:32 pm
> Subject: Re: [R] Fine tunning rgenoud
> To: R-help <r-help at stat.math.ethz.ch>
>
>
> > On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
> >  > It should be easy enough to check that your solution is valid
(i.e.
> > a local
> >  > minimum):  first, check to see if the solution satisfies all the
> >  > constraints; secondly, check to see if it is an interior point
> > (i.e. none of
> >  > the constraints become equality); and finally, if the solution
is an
> >  > interior point, check to see whether the gradient there is close
to
> > zero.
> >  > Note that if the solution is one of the vertices of the
polyhedron,
> > then the
> >  > gradient may not be zero.
> >
> >  I am having bad luck: all constraints are satisfied, but the solution
> >  given by constrOptim is not interior; the gradient is not equal to
> >  zero.
> >
> >  Paul
> >
> >
> >  > -----Original Message-----
> >  > From: r-help-bounces at stat.math.ethz.ch
> >  > [ On Behalf Of Paul Smith
> >  > Sent: Tuesday, July 03, 2007 5:10 PM
> >  > To: R-help
> >  > Subject: Re: [R] Fine tunning rgenoud
> >  >
> >  > On 7/3/07, Ravi Varadhan <rvaradhan at jhmi.edu> wrote:
> >  > > You had indicated in your previous email that you are
having trouble
> >  > finding
> >  > > a feasible starting value for constrOptim().  So, you
basically
> > need to
> >  > > solve a system of linear inequalities to obtain a starting
point.
> >  Have
> >  > you
> >  > > considered using linear programming? Either simplex() in
the "boot"
> >  > package
> >  > > or solveLP() in "linprog" would work.  It seems
to me that you
> > could use
> >  > any
> >  > > linear objective function in solveLP to obtain a feasible
> > starting point.
> >  > > This is not the most efficient solution, but it might be
worth a
> > try.
> >  > >
> >  > > I am aware of other methods for generating n-tuples that
satisfy
> > linear
> >  > > inequality constraints, but AFAIK those are not available
in R.
> >  >
> >  > Thanks, Ravi. I had already conceived the solution that you
suggest,
> >  > actually using "lpSolve". I am able to get a solution
for my problem
> >  > with constrOptim, but I am not enough confident that the
solution is
> >  > right. That is why I am trying to get a solution with rgenoud,
but
> >  > unsuccessfully until now.
> >  >
> >  > Paul
> >  >
> >  >
> >  >
> >  > > -----Original Message-----
> >  > > From: r-help-bounces at stat.math.ethz.ch
> >  > > [ On Behalf Of Paul Smith
> >  > > Sent: Tuesday, July 03, 2007 4:10 PM
> >  > > To: R-help
> >  > > Subject: [R] Fine tunning rgenoud
> >  > >
> >  > > Dear All,
> >  > >
> >  > > I am trying to solve the following maximization problem,
but I cannot
> >  > > have rgenoud giving me a reliable solution.
> >  > >
> >  > > Any ideas?
> >  > >
> >  > > Thanks in advance,
> >  > >
> >  > > Paul
> >  > >
> >  > > ----------------------------
> >  > > library(rgenoud)
> >  > >
> >  > > v <- 0.90
> >  > > O1 <- 10
> >  > > O2 <- 20
> >  > > O0 <- v*O1+(1-v)*O2
> >  > >
> >  > > myfunc <- function(x) {
> >  > >   U0 <- x[1]
> >  > >   U1 <- x[2]
> >  > >   U2 <- x[3]
> >  > >   q0 <- x[4]
> >  > >   q1 <- x[5]
> >  > >   q2 <- x[6]
> >  > >   p <- x[7]
> >  > >
> >  > >   if (U0 < 0)
> >  > >     return(-1e+200)
> >  > >   else if (U1 < 0)
> >  > >     return(-1e+200)
> >  > >   else if (U2 < 0)
> >  > >     return(-1e+200)
> >  > >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if((U2-(U0+(O0-O2)*q0)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if((U2-(U1+(O1-O2)*q1)) < 0)
> >  > >     return(-1e+200)
> >  > >   else if(p < 0)
> >  > >     return(-1e+200)
> >  > >   else if(p > 1)
> >  > >     return(-1e+200)
> >  > >   else if(q0 < 0)
> >  > >     return(-1e+200)
> >  > >   else if(q1 < 0)
> >  > >     return(-1e+200)
> >  > >   else if(q2 < 0)
> >  > >     return(-1e+200)
> >  > >   else
> >  > >
> >  >
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> >  > > )-(O2*q2+U2))))
> >  > >
> >  > > }
> >  > >
> >  >
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> >  > > rations=150,max.generations=300,boundary.enforcement=2)
> >  > >
> >  > > ______________________________________________
> >  > > R-help at stat.math.ethz.ch mailing list
> >  > >
> >  > > PLEASE do read the posting guide
> >  >
> >  > > and provide commented, minimal, self-contained,
reproducible code.
> >  > >
> >  >
> >  > ______________________________________________
> >  > R-help at stat.math.ethz.ch mailing list
> >  >
> >  > PLEASE do read the posting guide
> >  > and provide commented, minimal, self-contained, reproducible
code.
> >  >
> >
> >  ______________________________________________
> >  R-help at stat.math.ethz.ch mailing list
> >
> >  PLEASE do read the posting guide
> >  and provide commented, minimal, self-contained, reproducible code.
>
>

Paul Smith

2007-Jul-04 14:15 UTC

head link

[R] Fine tunning rgenoud

On 7/4/07, RAVI VARADHAN <rvaradhan at jhmi.edu>
wrote:> My point is that it might be better to try multiple (feasible) starting
values for constrOptim to ensure that you have a good local minimum, since it
appears that constrOptim converges to a boundary solution where the gradient is
non-zero.  That is why my code could be useful.
Thanks, Ravi. I have used your function, which works pretty fine.
However, constrOptim returns solutions markedly different, depending
on the starting values. That is true that I am expecting a solution in
the boundary, but should not constrOptim find boundary solutions
correctly? The set of solution that I got is below.

Paul

--------------------------------

2.67682495728743e-08	0.676401684216637	5.18627076390355e-09	0.00206463986063195
0.87185968612836	4.32039325909089e-11	0.999999999996234
3.71711020733097e-08	0.539853580957444	1.82592937615235e-08	0.00206941041763503
0.93305250393447	2.08076621230984e-11	0.999999999995774
1.55648443014316e-08	0.356047772992972	8.61341165816411e-09	0.00207149128044574
0.939531540703735	2.55211186629222e-12	0.999999999999424
2.20685747493755e-07	0.575689534431218	5.30976753476747e-08	0.00210500604605837
0.588947341576757	3.1310360048386e-10	0.999999999998789
1.92961662926727e-08	0.773588030510204	1.04841835042200e-08	0.00206723852358352
0.816755014708394	3.89478290348532e-11	0.999999999997794
0.000279824051289082	0.000310992385522886	1.01467522935252e-06
3.11645639181419e-05	0.00249801538651552	3.0978819115532e-05
7.11821104872585e-06
2.81901448690893e-07	0.381718731525906	4.72860507882539e-08	0.00206807672109157
0.769178513763055	1.39278079797628e-09	0.999999999967123
5.58938545019597e-05	0.00171253668169328	4.54005998518212e-09
0.00165663757292733	0.00247994862102590	6.20992250482468e-06	0.419169641865998
1.03300938985890e-08	0.438357835603591	6.89854079723234e-09	0.00206693286138396
0.977554885433201	1.17209206267609e-10	0.99999999996921
7.63336821363444e-05	0.00177141538041517	1.88050423143828e-10
0.00169507950991094	0.00249739505142207	8.4814984916537e-06	0.470929220605509
9.16005846107533e-09	0.682179815036755	1.63255733785783e-09	0.00206922107327189
0.919323193130209	5.71436138398897e-11	0.99999999999629
1.40968913167328e-08	0.343606628343661	1.33227447885302e-08	0.00206789984370423
0.343671264496824	1.11679312116211e-11	0.999999999999822
4.76054734844857e-09	0.593022549313178	2.28102966623129e-09	0.00206625165098398
0.947562121256448	8.9437610753173e-11	0.999999999999992
1.96950784184139e-07	0.579488113726155	1.61915231214025e-07	0.00208000350528798
1.00891340595040	1.22248906754713e-10	0.999999999996493
8.1448937742933e-09	0.441088618716555	4.54846390087941e-09	0.00207634940425852
0.446155700100820	4.81439647816238e-12	0.99999999999939
4.82439218405912e-08	0.557771049256698	3.53737879481732e-08	0.0020663035737319
0.588137767965923	2.6568947800491e-11	0.999999999988615
2.43086751126363e-08	0.522927598354163	2.26886829089137e-08	0.00206533531066324
0.611696593543814	4.51226610050184e-11	0.999999999999087
3.05498959434100e-08	0.465522202845817	1.09246302124670e-08	0.00207004066920179
0.465583376966915	3.24213847202457e-11	0.999999999997366
1.88687179088788e-07	0.783614197203923	4.51346471059839e-08	0.00222403775221293
0.786422171740329	8.17865794171933e-10	0.999999999986103
1.0154423824979e-08	0.302657777579883	9.06923080122203e-09	0.00206615353968094
0.359722316646974	8.27866320956902e-12	0.99999999998461
8.91008717665837e-08	0.0020661526864997	3.08619455858999e-09	0.00206579199039568
0.00275523149199496	9.55650084108725e-09	0.985185595958656
1.25320647920029e-07	0.635217955401437	7.44627883600107e-08	0.00206656250455391
0.855937507707323	3.70326032870889e-10	0.999999999998375
2.57618374406559e-08	0.636499151952225	1.09822023878715e-08	0.00206677354204888
0.772636071860102	8.99370944431481e-11	0.999999999978744
1.09474196877990e-08	0.501469973722704	1.19992915868609e-10	0.00206117941606503
0.501594064757161	1.34320044786225e-11	0.999999999991232
5.24203710193977e-05	0.000127998340144109	3.33258623630601e-09
7.55779680724378e-05	0.00248898574263025	5.82411313482383e-06	0.0221497278110802
3.80217498132259e-07	0.57664568703189	1.01755510162620e-08	0.00207232950382402
0.944031557945531	5.30703662426069e-10	0.999999999995957
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2.64911355650347e-05	0.00259858019547791	2.64749446522330e-05
1.83580740341509e-07
7.39730651399581e-10	0.00908091738218919	2.48425610406978e-10
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1.89137722020867e-08	0.611106915103611	3.89703191870382e-09	0.00210184590871973
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1.71605199821395e-06
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0.864714866878808	3.50701456652884e-10	0.999999999999926
4.72130896241037e-09	0.193480077858215	4.09642232386814e-09	0.00206639690357456
0.193772609031377	2.22379321541448e-11	0.999999999992884
3.55665252909232e-08	0.620669750121032	1.90641809388101e-08	0.00206864461846135
0.622207402604423	3.55684392133601e-11	0.999999999999635
3.43643575170166e-08	0.508032144170851	3.05576064051123e-08	0.0020666442030495
0.537473527046566	5.41317633959989e-12	0.999999999991207
2.07413577081273e-08	0.517006009937055	1.78794895322523e-08	0.00206609160101216
0.723546217083115	4.25770563404542e-11	0.999999999977351
2.9634111809255e-08	0.678167734702809	2.87136255305397e-08	0.00207005922065176
0.680058941948453	4.86294997869349e-11	0.999999999997674
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0.821904778895813	2.72480529179635e-10	0.999999999999417
1.21638582096581e-05	0.685066257234478	3.90995182181942e-06	0.00201558375343728
0.685516429216796	4.73765370536012e-08	0.999999999999993
6.21341332802845e-08	0.45153366532873	4.28836207599489e-08	0.00205228864113157
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1.19446880731148e-06	0.00204849378641721	5.41758686583886e-10
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4.23724996341138e-07	0.76589882078562	1.07976473375288e-07	0.00231084075578484
0.772123021534594	4.222800306051e-09	0.99999999999554
9.76490929801592e-09	0.611133237912937	3.40654501481527e-09	0.00206753317060016
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1.00090667437022e-05
4.87431144092831e-09	0.486985270937825	1.01147265793908e-09	0.00206873578985202
0.494229783529316	2.1163667211661e-12	0.999999999999217
1.58678140422157e-08	0.458475824861338	3.728478508397e-09	0.00206665340523142
0.822538576890515	6.73647051811321e-11	0.999999999992949
7.78797943133767e-07	0.00201714819466376	1.00271036821046e-09
0.00201517307886584	0.00243247068677390	8.6420943116519e-08	0.946415585057681
1.79734244345473e-07	0.618114350664356	8.41196223101054e-08	0.00209424634015987
1.09808725088463	1.36311179064841e-09	0.999999999999325
4.04750622932535e-06	0.00202435649740235	9.55231839434103e-11
0.00202030658534268	0.00249780762721203	4.49711157881299e-07	0.878051982789172
3.27944009298396e-08	0.710329613922295	2.02989735589882e-08	0.00206702754480486
0.713789321637634	4.43500632164969e-12	0.99999999998325
3.6211203640154e-08	0.486990872484964	2.23029819494578e-08	0.00206834819984283
0.925447188571729	1.43913590315638e-10	0.999999999999852
1.52117049757253e-08	0.499368102973816	5.70289700988348e-09	0.00206632041653347
0.688163413575525	6.86450078797379e-11	0.99999999998881
2.14084286484963e-08	0.669902287842233	1.64604388157258e-08	0.00206787121557579
0.675669448264383	3.05725070183645e-11	0.99999999999783
4.64383080200508e-05	0.00188125145190771	2.92580309919556e-10
0.00183481310287054	0.00250971056566956	5.15977640139516e-06	0.571340025768215
3.11099577796555e-08	0.319299482089934	8.84023352637676e-09	0.00206855023112842
0.441077204370492	1.10446087116967e-09	0.999999999995467
0.000102965203269986	0.0016493488546921	2.58445958349384e-10	0.00154638327053218
0.00250288634336625	1.14405481683120e-05	0.342341363715383
5.87912519479874e-09	0.00301357388024528	2.75211293457077e-10
0.00206603126487256	0.00686204622812863	6.1682829968701e-10	0.999931564740833
8.28694064868836e-08	0.673413934917665	5.55691871872657e-08	0.00206648968616976
0.690994737517309	8.53762213679993e-11	0.99999999999553
2.78964308878308e-08	0.631906605077265	1.87081150212841e-08	0.00206682302780812
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2.09286186935030e-05	0.00249989443096258	2.06676012144089e-05
2.57319855839169e-06
5.79914576203232e-05	0.00181271191072469	1.15884908131972e-09
0.00175471081855071	0.0024812702174432	6.44334507197721e-06	0.509698530097913
2.0503183260964e-08	0.546450460261978	1.27059638843222e-08	0.00206791702172114
1.14082199649402	8.5751965370755e-12	0.99999999999683
3.66836690280629e-08	0.481874078118496	3.13611734401948e-08	0.00207354422550728
0.990376379663234	2.13707863395726e-10	0.999999999975761
1.77224405556878e-08	0.493128575789259	8.63845133717168e-09	0.00207307974398005
0.493553411995952	3.19150428367562e-11	0.999999999999902
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1.91321783130778e-07	0.00205131977291163	2.45737561775750e-10
0.00205112100576657	0.00251498989989795	2.12303674145017e-08	0.981038377325434
2.04970869809e-09	0.61540968024267	1.80692316850342e-10	0.00206758160218205
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2.28380664111838e-07	0.495196927735637	2.03520983522517e-07	0.00206484911183903
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0.000142663207352814	0.00136226156979156	2.47224893929883e-11
0.00121959537442013	0.00249964872330666	1.58514632925203e-05	0.213308634647407


> ----- Original Message -----
> From: Paul Smith <phhs80 at gmail.com>
> Date: Wednesday, July 4, 2007 6:00 am
> Subject: Re: [R] Fine tunning rgenoud
> To: R-help <r-help at stat.math.ethz.ch>
>
>
> > On 7/4/07, RAVI VARADHAN <rvaradhan at jhmi.edu> wrote:
> >  > Here is another approach: I wrote an R function that would
generate
> > interior points as starting values for constrOptim.  This might work
> > better than the LP approach, since the LP approach gives you a
> > starting value that is on the boundary of the feasible region, i.e a
> > vertex of the polyhedron, whereas this new approach gives you points
> > on the interior.  You can generate as many points as you wish, but the
> > approach is brute-force and is very inefficient - it takes on the
> > order of a 1000 tries to find one feasible point.
> >
> >  Thanks again, Ravi. Actually, the LP approach also works here. Let
> >  g(X) >= k be the constraints. Then, by solving a LP problem with
the
> >  constraints
> >
> >  g(X) >= (k+0.2)
> >
> >  returns an interior starting value for constrOptim. I am aware that
> >  the new set of constraints may correspond to an impossible linear
> >  system, but it works in many cases.
> >
> >  Paul
> >
> >  > ----- Original Message -----
> >  > From: Paul Smith <phhs80 at gmail.com>
> >  > Date: Tuesday, July 3, 2007 7:32 pm
> >  > Subject: Re: [R] Fine tunning rgenoud
> >  > To: R-help <r-help at stat.math.ethz.ch>
> >  >
> >  >
> >  > > On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:
> >  > >  > It should be easy enough to check that your solution
is valid
> > (i.e.
> >  > > a local
> >  > >  > minimum):  first, check to see if the solution
satisfies all the
> >  > >  > constraints; secondly, check to see if it is an
interior point
> >  > > (i.e. none of
> >  > >  > the constraints become equality); and finally, if the
solution
> > is an
> >  > >  > interior point, check to see whether the gradient
there is
> > close to
> >  > > zero.
> >  > >  > Note that if the solution is one of the vertices of
the polyhedron,
> >  > > then the
> >  > >  > gradient may not be zero.
> >  > >
> >  > >  I am having bad luck: all constraints are satisfied, but
the solution
> >  > >  given by constrOptim is not interior; the gradient is not
equal
> > to
> >  > >  zero.
> >  > >
> >  > >  Paul
> >  > >
> >  > >
> >  > >  > -----Original Message-----
> >  > >  > From: r-help-bounces at stat.math.ethz.ch
> >  > >  > [ On Behalf Of Paul Smith
> >  > >  > Sent: Tuesday, July 03, 2007 5:10 PM
> >  > >  > To: R-help
> >  > >  > Subject: Re: [R] Fine tunning rgenoud
> >  > >  >
> >  > >  > On 7/3/07, Ravi Varadhan <rvaradhan at
jhmi.edu> wrote:
> >  > >  > > You had indicated in your previous email that
you are having
> > trouble
> >  > >  > finding
> >  > >  > > a feasible starting value for constrOptim(). 
So, you basically
> >  > > need to
> >  > >  > > solve a system of linear inequalities to obtain
a starting point.
> >  > >  Have
> >  > >  > you
> >  > >  > > considered using linear programming? Either
simplex() in the
> > "boot"
> >  > >  > package
> >  > >  > > or solveLP() in "linprog" would work. 
It seems to me that you
> >  > > could use
> >  > >  > any
> >  > >  > > linear objective function in solveLP to obtain a
feasible
> >  > > starting point.
> >  > >  > > This is not the most efficient solution, but it
might be
> > worth a
> >  > > try.
> >  > >  > >
> >  > >  > > I am aware of other methods for generating
n-tuples that satisfy
> >  > > linear
> >  > >  > > inequality constraints, but AFAIK those are not
available in
> > R.
> >  > >  >
> >  > >  > Thanks, Ravi. I had already conceived the solution
that you suggest,
> >  > >  > actually using "lpSolve". I am able to get
a solution for my problem
> >  > >  > with constrOptim, but I am not enough confident that
the
> > solution is
> >  > >  > right. That is why I am trying to get a solution with
rgenoud,
> > but
> >  > >  > unsuccessfully until now.
> >  > >  >
> >  > >  > Paul
> >  > >  >
> >  > >  >
> >  > >  >
> >  > >  > > -----Original Message-----
> >  > >  > > From: r-help-bounces at stat.math.ethz.ch
> >  > >  > > [ On Behalf Of Paul Smith
> >  > >  > > Sent: Tuesday, July 03, 2007 4:10 PM
> >  > >  > > To: R-help
> >  > >  > > Subject: [R] Fine tunning rgenoud
> >  > >  > >
> >  > >  > > Dear All,
> >  > >  > >
> >  > >  > > I am trying to solve the following maximization
problem, but
> > I cannot
> >  > >  > > have rgenoud giving me a reliable solution.
> >  > >  > >
> >  > >  > > Any ideas?
> >  > >  > >
> >  > >  > > Thanks in advance,
> >  > >  > >
> >  > >  > > Paul
> >  > >  > >
> >  > >  > > ----------------------------
> >  > >  > > library(rgenoud)
> >  > >  > >
> >  > >  > > v <- 0.90
> >  > >  > > O1 <- 10
> >  > >  > > O2 <- 20
> >  > >  > > O0 <- v*O1+(1-v)*O2
> >  > >  > >
> >  > >  > > myfunc <- function(x) {
> >  > >  > >   U0 <- x[1]
> >  > >  > >   U1 <- x[2]
> >  > >  > >   U2 <- x[3]
> >  > >  > >   q0 <- x[4]
> >  > >  > >   q1 <- x[5]
> >  > >  > >   q2 <- x[6]
> >  > >  > >   p <- x[7]
> >  > >  > >
> >  > >  > >   if (U0 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if (U1 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if (U2 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if((U2-(U0+(O0-O2)*q0)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if((U2-(U1+(O1-O2)*q1)) < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if(p < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if(p > 1)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if(q0 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if(q1 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else if(q2 < 0)
> >  > >  > >     return(-1e+200)
> >  > >  > >   else
> >  > >  > >
> >  > >  >
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> >  > >  > > )-(O2*q2+U2))))
> >  > >  > >
> >  > >  > > }
> >  > >  > >
> >  > >  >
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> >  > >  > >
rations=150,max.generations=300,boundary.enforcement=2)
> >  > >  > >
> >  > >  > > ______________________________________________
> >  > >  > > R-help at stat.math.ethz.ch mailing list
> >  > >  > >
> >  > >  > > PLEASE do read the posting guide
> >  > >  >
> >  > >  > > and provide commented, minimal, self-contained,
reproducible
> > code.
> >  > >  > >
> >  > >  >
> >  > >  > ______________________________________________
> >  > >  > R-help at stat.math.ethz.ch mailing list
> >  > >  >
> >  > >  > PLEASE do read the posting guide
> >  > >  > and provide commented, minimal, self-contained,
reproducible code.
> >  > >  >
> >  > >
> >  > >  ______________________________________________
> >  > >  R-help at stat.math.ethz.ch mailing list
> >  > >
> >  > >  PLEASE do read the posting guide
> >  > >  and provide commented, minimal, self-contained,
reproducible code.
> >  >
> >  >
> >
> >  ______________________________________________
> >  R-help at stat.math.ethz.ch mailing list
> >
> >  PLEASE do read the posting guide
> >  and provide commented, minimal, self-contained, reproducible code.
>

Paul Smith

2007-Jul-04 14:22 UTC

head link

[R] Fine tunning rgenoud

On 7/4/07, Paul Smith <phhs80 at gmail.com> wrote:> On 7/4/07, RAVI VARADHAN <rvaradhan at jhmi.edu> wrote:
> > My point is that it might be better to try multiple (feasible)
starting values for constrOptim to ensure that you have a good local minimum,
since it appears that constrOptim converges to a boundary solution where the
gradient is non-zero.  That is why my code could be useful.
>
> Thanks, Ravi. I have used your function, which works pretty fine.
> However, constrOptim returns solutions markedly different, depending
> on the starting values. That is true that I am expecting a solution in
> the boundary, but should not constrOptim find boundary solutions
> correctly? The set of solution that I got is below.
Unless, there are many local optimal solutions...

Paul

> --------------------------------
>
> 2.67682495728743e-08    0.676401684216637       5.18627076390355e-09   
0.00206463986063195     0.87185968612836        4.32039325909089e-11   
0.999999999996234
> 3.71711020733097e-08    0.539853580957444       1.82592937615235e-08   
0.00206941041763503     0.93305250393447        2.08076621230984e-11   
0.999999999995774
> 1.55648443014316e-08    0.356047772992972       8.61341165816411e-09   
0.00207149128044574     0.939531540703735       2.55211186629222e-12   
0.999999999999424
> 2.20685747493755e-07    0.575689534431218       5.30976753476747e-08   
0.00210500604605837     0.588947341576757       3.1310360048386e-10    
0.999999999998789
> 1.92961662926727e-08    0.773588030510204       1.04841835042200e-08   
0.00206723852358352     0.816755014708394       3.89478290348532e-11   
0.999999999997794
> 0.000279824051289082    0.000310992385522886    1.01467522935252e-06   
3.11645639181419e-05    0.00249801538651552     3.0978819115532e-05    
7.11821104872585e-06
> 2.81901448690893e-07    0.381718731525906       4.72860507882539e-08   
0.00206807672109157     0.769178513763055       1.39278079797628e-09   
0.999999999967123
> 5.58938545019597e-05    0.00171253668169328     4.54005998518212e-09   
0.00165663757292733     0.00247994862102590     6.20992250482468e-06   
0.419169641865998
> 1.03300938985890e-08    0.438357835603591       6.89854079723234e-09   
0.00206693286138396     0.977554885433201       1.17209206267609e-10   
0.99999999996921
> 7.63336821363444e-05    0.00177141538041517     1.88050423143828e-10   
0.00169507950991094     0.00249739505142207     8.4814984916537e-06    
0.470929220605509
> 9.16005846107533e-09    0.682179815036755       1.63255733785783e-09   
0.00206922107327189     0.919323193130209       5.71436138398897e-11   
0.99999999999629
> 1.40968913167328e-08    0.343606628343661       1.33227447885302e-08   
0.00206789984370423     0.343671264496824       1.11679312116211e-11   
0.999999999999822
> 4.76054734844857e-09    0.593022549313178       2.28102966623129e-09   
0.00206625165098398     0.947562121256448       8.9437610753173e-11    
0.999999999999992
> 1.96950784184139e-07    0.579488113726155       1.61915231214025e-07   
0.00208000350528798     1.00891340595040        1.22248906754713e-10   
0.999999999996493
> 8.1448937742933e-09     0.441088618716555       4.54846390087941e-09   
0.00207634940425852     0.446155700100820       4.81439647816238e-12   
0.99999999999939
> 4.82439218405912e-08    0.557771049256698       3.53737879481732e-08   
0.0020663035737319      0.588137767965923       2.6568947800491e-11    
0.999999999988615
> 2.43086751126363e-08    0.522927598354163       2.26886829089137e-08   
0.00206533531066324     0.611696593543814       4.51226610050184e-11   
0.999999999999087
> 3.05498959434100e-08    0.465522202845817       1.09246302124670e-08   
0.00207004066920179     0.465583376966915       3.24213847202457e-11   
0.999999999997366
> 1.88687179088788e-07    0.783614197203923       4.51346471059839e-08   
0.00222403775221293     0.786422171740329       8.17865794171933e-10   
0.999999999986103
> 1.0154423824979e-08     0.302657777579883       9.06923080122203e-09   
0.00206615353968094     0.359722316646974       8.27866320956902e-12   
0.99999999998461
> 8.91008717665837e-08    0.0020661526864997      3.08619455858999e-09   
0.00206579199039568     0.00275523149199496     9.55650084108725e-09   
0.985185595958656
> 1.25320647920029e-07    0.635217955401437       7.44627883600107e-08   
0.00206656250455391     0.855937507707323       3.70326032870889e-10   
0.999999999998375
> 2.57618374406559e-08    0.636499151952225       1.09822023878715e-08   
0.00206677354204888     0.772636071860102       8.99370944431481e-11   
0.999999999978744
> 1.09474196877990e-08    0.501469973722704       1.19992915868609e-10   
0.00206117941606503     0.501594064757161       1.34320044786225e-11   
0.999999999991232
> 5.24203710193977e-05    0.000127998340144109    3.33258623630601e-09   
7.55779680724378e-05    0.00248898574263025     5.82411313482383e-06   
0.0221497278110802
> 3.80217498132259e-07    0.57664568703189        1.01755510162620e-08   
0.00207232950382402     0.944031557945531       5.30703662426069e-10   
0.999999999995957
> 1.45159816281038e-09    0.391742001993341       1.13492553980291e-09   
0.00206615324883312     0.73041632635671        2.05351961803669e-11   
0.99999999997684
> 8.74006318627465e-05    0.00176059707830211     1.94489765002966e-09   
0.00167319599216734     0.00234472182706612     9.710963192258e-06     
0.358282221037878
> 0.000238275046444342    0.000264776586825777    4.40904795740029e-10   
2.64911355650347e-05    0.00259858019547791     2.64749446522330e-05   
1.83580740341509e-07
> 7.39730651399581e-10    0.00908091738218919     2.48425610406978e-10   
0.00206667909063917     0.00928420674840742     5.18131986840764e-11   
0.99999875366957
> 6.76489417503509e-08    0.66948409231674        3.03852881114497e-08   
0.00207327594614506     0.82038550137061        2.64031575134214e-11   
0.999999999984622
> 2.47578596556463e-05    0.00192273935278028     1.23710433232059e-10   
0.00189797520967688     0.00249714264227544     2.75085723641778e-06   
0.654395200885401
> 1.89137722020867e-08    0.611106915103611       3.89703191870382e-09   
0.00210184590871973     0.624411027730728       8.5135512646264e-11    
0.99999999999684
> 0.00019176743398086     0.000561608946531094    3.86469382998825e-10   
0.000369840972771214    0.00250444089363261     2.13074457599853e-05   
0.0571352017772342
> 0.000185606084629350    0.000206269128591342    1.56795453162326e-11   
2.06627190417154e-05    0.00249993097016385     2.06228887085015e-05   
1.71605199821395e-06
> 6.07957336199056e-08    0.483682520205442       5.5863930138716e-09    
0.00206322767692575     0.483682695616455       5.34362969147144e-11   
0.999999999999643
> 2.32535804244419e-08    0.479995736120651       1.71422519965926e-08   
0.00207338945556393     0.510141538832558       1.48964674702430e-11   
0.999999999993732
> 8.9183702782689e-06     0.00206653282852738     1.75762003328053e-10   
0.00205761314408722     0.00252353219843752     9.9090949737504e-07    
0.833268509557228
> 1.98549228223182e-06    0.251617257564206       1.05359270191879e-06   
0.0022260243792503      0.251624161164046       9.60072596752024e-08   
0.99999999999983
> 3.98028438135354e-08    0.547004412551238       3.46420325883517e-08   
0.00206593124574590     0.780233389945956       4.31912137883551e-11   
0.999999999999248
> 7.415833973742e-09      0.411955745727431       6.63826778226352e-09   
0.00206692655795474     0.422974654599724       6.0360458732987e-12    
0.999999999999735
> 2.31198818168677e-09    0.00651214491263961     1.32346818065092e-09   
0.00206600061742381     0.0308298577099849      1.09702273280814e-10   
0.99987783901442
> 4.17312889043775e-08    0.535841994679291       2.16650907799191e-08   
0.00206804295529002     0.59999577506709        1.18576996500002e-10   
0.999999999999237
> 3.06571185479614e-08    0.210504230265054       2.05714086443132e-08   
0.00206707615217700     0.218748559037881       2.15131848511398e-14   
0.999999999993557
> 2.75615889053932e-09    0.410462493146348       1.61078464820130e-09   
0.00206420001019636     0.410565659594555       9.40738331890563e-11   
0.999999999999952
> 4.56613193593397e-09    0.408415058997493       2.33397373332447e-09   
0.00206711241339086     0.532349316444773       6.74887208834456e-11   
0.99999999999929
> 7.18189347926295e-08    0.456169544603848       5.38996419605601e-08   
0.00206990174706466     1.10900729793115        1.09308927282691e-13   
0.999999999990783
> 0.000188732057072893    0.000209745553735604    2.65570357321341e-11   
2.10123232762018e-05    0.00249946399527847     2.09702247828353e-05   
7.56804739408697e-07
> 5.85086685972612e-08    0.586106422015639       3.34740271798516e-08   
0.00207017375045705     1.02476378656892        7.7586558103274e-11    
0.999999999999751
> 0.000110963331385117    0.000134315151780862    1.07242866306447e-06   
2.33497881113803e-05    0.00255535434807175     1.22100977811675e-05   
0.0100715104652649
> 6.74756547544261e-05    0.00181277651670570     2.06882429964314e-10   
0.0017453002881811      0.00248364499775618     7.49727080120661e-06   
0.477865304416143
> 2.12169576142447e-09    0.258696699048681       3.83834275215625e-10   
0.00206572907235368     0.593016720449582       2.47234004478185e-11   
0.999999999976093
> 4.90290042793427e-08    0.845133894257049       4.26659941495083e-08   
0.00206573635916222     0.846607006638287       2.63753283209851e-10   
0.999999999994938
> 1.82215438136793e-08    0.80366504831158        1.78340820866931e-08   
0.00225471081235068     0.805133180734986       2.65837229120276e-12   
0.999999999992972
> 4.73449331282602e-08    0.284890209400889       3.18447541813436e-08   
0.00206840481685483     0.808166776706798       4.05949074947464e-10   
0.999999999996061
> 1.09692979675704e-08    0.504203767689845       1.91188777015599e-09   
0.00206788476221373     0.706912076703946       4.06894266747559e-11   
0.99999999999973
> 4.34112012988195e-08    0.458125660334097       6.46770375936903e-09   
0.00207007623328698     0.625303714142111       1.01347377674089e-10   
0.999999999992636
> 1.16509068624767e-07    0.598772124413396       1.83783072861908e-08   
0.00207311616484422     0.649412674861061       1.72090788969858e-10   
0.999999999982887
> 1.72904399298124e-08    0.58859841513479        5.56864060572789e-09   
0.00206902943325815     0.834770114923498       4.44826394221343e-11   
0.999999999998404
> 1.95167889112074e-07    0.680051903362475       4.07870548730064e-08   
0.0021048787521164      0.758987053084469       3.35901569072651e-10   
0.999999999999464
> 1.06657670445553e-08    0.705185947467634       5.468246700687e-09     
0.00206717328235464     0.852353580488024       9.79781097317382e-11   
0.999999999997673
> 3.38906655480421e-08    0.675066389889348       5.7356420037523e-09    
0.00206939927716748     0.864714866878808       3.50701456652884e-10   
0.999999999999926
> 4.72130896241037e-09    0.193480077858215       4.09642232386814e-09   
0.00206639690357456     0.193772609031377       2.22379321541448e-11   
0.999999999992884
> 3.55665252909232e-08    0.620669750121032       1.90641809388101e-08   
0.00206864461846135     0.622207402604423       3.55684392133601e-11   
0.999999999999635
> 3.43643575170166e-08    0.508032144170851       3.05576064051123e-08   
0.0020666442030495      0.537473527046566       5.41317633959989e-12   
0.999999999991207
> 2.07413577081273e-08    0.517006009937055       1.78794895322523e-08   
0.00206609160101216     0.723546217083115       4.25770563404542e-11   
0.999999999977351
> 2.9634111809255e-08     0.678167734702809       2.87136255305397e-08   
0.00207005922065176     0.680058941948453       4.86294997869349e-11   
0.999999999997674
> 2.70007729246723e-08    0.777109777637737       2.23198659183296e-08   
0.00211784135373727     0.821904778895813       2.72480529179635e-10   
0.999999999999417
> 1.21638582096581e-05    0.685066257234478       3.90995182181942e-06   
0.00201558375343728     0.685516429216796       4.73765370536012e-08   
0.999999999999993
> 6.21341332802845e-08    0.45153366532873        4.28836207599489e-08   
0.00205228864113157     0.630886659065685       2.01031448944481e-10   
0.999999999976095
> 1.19446880731148e-06    0.00204849378641721     5.41758686583886e-10   
0.00204660358124349     0.00250002927315376     1.32657483581135e-07   
0.926358671695374
> 4.23724996341138e-07    0.76589882078562        1.07976473375288e-07   
0.00231084075578484     0.772123021534594       4.222800306051e-09     
0.99999999999554
> 9.76490929801592e-09    0.611133237912937       3.40654501481527e-09   
0.00206753317060016     0.624278286034974       1.35688861199835e-11   
0.999999999991987
> 0.000185800168507657    0.000206604414024173    1.51257663200075e-10   
2.08040548465085e-05    0.00249987187225613     2.06444402710859e-05   
1.00090667437022e-05
> 4.87431144092831e-09    0.486985270937825       1.01147265793908e-09   
0.00206873578985202     0.494229783529316       2.1163667211661e-12    
0.999999999999217
> 1.58678140422157e-08    0.458475824861338       3.728478508397e-09     
0.00206665340523142     0.822538576890515       6.73647051811321e-11   
0.999999999992949
> 7.78797943133767e-07    0.00201714819466376     1.00271036821046e-09   
0.00201517307886584     0.00243247068677390     8.6420943116519e-08    
0.946415585057681
> 1.79734244345473e-07    0.618114350664356       8.41196223101054e-08   
0.00209424634015987     1.09808725088463        1.36311179064841e-09   
0.999999999999325
> 4.04750622932535e-06    0.00202435649740235     9.55231839434103e-11   
0.00202030658534268     0.00249780762721203     4.49711157881299e-07   
0.878051982789172
> 3.27944009298396e-08    0.710329613922295       2.02989735589882e-08   
0.00206702754480486     0.713789321637634       4.43500632164969e-12   
0.99999999998325
> 3.6211203640154e-08     0.486990872484964       2.23029819494578e-08   
0.00206834819984283     0.925447188571729       1.43913590315638e-10   
0.999999999999852
> 1.52117049757253e-08    0.499368102973816       5.70289700988348e-09   
0.00206632041653347     0.688163413575525       6.86450078797379e-11   
0.99999999998881
> 2.14084286484963e-08    0.669902287842233       1.64604388157258e-08   
0.00206787121557579     0.675669448264383       3.05725070183645e-11   
0.99999999999783
> 4.64383080200508e-05    0.00188125145190771     2.92580309919556e-10   
0.00183481310287054     0.00250971056566956     5.15977640139516e-06   
0.571340025768215
> 3.11099577796555e-08    0.319299482089934       8.84023352637676e-09   
0.00206855023112842     0.441077204370492       1.10446087116967e-09   
0.999999999995467
> 0.000102965203269986    0.0016493488546921      2.58445958349384e-10   
0.00154638327053218     0.00250288634336625     1.14405481683120e-05   
0.342341363715383
> 5.87912519479874e-09    0.00301357388024528     2.75211293457077e-10   
0.00206603126487256     0.00686204622812863     6.1682829968701e-10    
0.999931564740833
> 8.28694064868836e-08    0.673413934917665       5.55691871872657e-08   
0.00206648968616976     0.690994737517309       8.53762213679993e-11   
0.99999999999553
> 2.78964308878308e-08    0.631906605077265       1.87081150212841e-08   
0.00206682302780812     1.04912853459322        1.19798263785958e-10   
0.999999999998404
> 0.000186009655330342    0.000206938973112988    1.18525336022574e-09   
2.09286186935030e-05    0.00249989443096258     2.06676012144089e-05   
2.57319855839169e-06
> 5.79914576203232e-05    0.00181271191072469     1.15884908131972e-09   
0.00175471081855071     0.0024812702174432      6.44334507197721e-06   
0.509698530097913
> 2.0503183260964e-08     0.546450460261978       1.27059638843222e-08   
0.00206791702172114     1.14082199649402        8.5751965370755e-12    
0.99999999999683
> 3.66836690280629e-08    0.481874078118496       3.13611734401948e-08   
0.00207354422550728     0.990376379663234       2.13707863395726e-10   
0.999999999975761
> 1.77224405556878e-08    0.493128575789259       8.63845133717168e-09   
0.00207307974398005     0.493553411995952       3.19150428367562e-11   
0.999999999999902
> 0.000119234853016321    0.00194143059603129     2.65621637099599e-10   
0.00182214114564480     0.00258385562559042     1.32482776896270e-05   
0.564809333872708
> 1.91321783130778e-07    0.00205131977291163     2.45737561775750e-10   
0.00205112100576657     0.00251498989989795     2.12303674145017e-08   
0.981038377325434
> 2.04970869809e-09       0.61540968024267        1.80692316850342e-10   
0.00206758160218205     0.616881623876956       9.88879753424694e-11   
0.999999999998682
> 2.28380664111838e-07    0.495196927735637       2.03520983522517e-07   
0.00206484911183903     0.495729865740038       3.10063601627842e-10   
0.999999999998029
> 0.000142663207352814    0.00136226156979156     2.47224893929883e-11   
0.00121959537442013     0.00249964872330666     1.58514632925203e-05   
0.213308634647407
>
>
>
> > ----- Original Message -----
> > From: Paul Smith <phhs80 at gmail.com>
> > Date: Wednesday, July 4, 2007 6:00 am
> > Subject: Re: [R] Fine tunning rgenoud
> > To: R-help <r-help at stat.math.ethz.ch>
> >
> >
> > > On 7/4/07, RAVI VARADHAN <rvaradhan at jhmi.edu> wrote:
> > >  > Here is another approach: I wrote an R function that would
generate
> > > interior points as starting values for constrOptim.  This might
work
> > > better than the LP approach, since the LP approach gives you a
> > > starting value that is on the boundary of the feasible region,
i.e a
> > > vertex of the polyhedron, whereas this new approach gives you
points
> > > on the interior.  You can generate as many points as you wish,
but the
> > > approach is brute-force and is very inefficient - it takes on the
> > > order of a 1000 tries to find one feasible point.
> > >
> > >  Thanks again, Ravi. Actually, the LP approach also works here.
Let
> > >  g(X) >= k be the constraints. Then, by solving a LP problem
with the
> > >  constraints
> > >
> > >  g(X) >= (k+0.2)
> > >
> > >  returns an interior starting value for constrOptim. I am aware
that
> > >  the new set of constraints may correspond to an impossible
linear
> > >  system, but it works in many cases.
> > >
> > >  Paul
> > >
> > >  > ----- Original Message -----
> > >  > From: Paul Smith <phhs80 at gmail.com>
> > >  > Date: Tuesday, July 3, 2007 7:32 pm
> > >  > Subject: Re: [R] Fine tunning rgenoud
> > >  > To: R-help <r-help at stat.math.ethz.ch>
> > >  >
> > >  >
> > >  > > On 7/4/07, Ravi Varadhan <rvaradhan at jhmi.edu>
wrote:
> > >  > >  > It should be easy enough to check that your
solution is valid
> > > (i.e.
> > >  > > a local
> > >  > >  > minimum):  first, check to see if the solution
satisfies all the
> > >  > >  > constraints; secondly, check to see if it is an
interior point
> > >  > > (i.e. none of
> > >  > >  > the constraints become equality); and finally,
if the solution
> > > is an
> > >  > >  > interior point, check to see whether the
gradient there is
> > > close to
> > >  > > zero.
> > >  > >  > Note that if the solution is one of the vertices
of the polyhedron,
> > >  > > then the
> > >  > >  > gradient may not be zero.
> > >  > >
> > >  > >  I am having bad luck: all constraints are satisfied,
but the solution
> > >  > >  given by constrOptim is not interior; the gradient is
not equal
> > > to
> > >  > >  zero.
> > >  > >
> > >  > >  Paul
> > >  > >
> > >  > >
> > >  > >  > -----Original Message-----
> > >  > >  > From: r-help-bounces at stat.math.ethz.ch
> > >  > >  > [ On Behalf Of Paul Smith
> > >  > >  > Sent: Tuesday, July 03, 2007 5:10 PM
> > >  > >  > To: R-help
> > >  > >  > Subject: Re: [R] Fine tunning rgenoud
> > >  > >  >
> > >  > >  > On 7/3/07, Ravi Varadhan <rvaradhan at
jhmi.edu> wrote:
> > >  > >  > > You had indicated in your previous email
that you are having
> > > trouble
> > >  > >  > finding
> > >  > >  > > a feasible starting value for
constrOptim().  So, you basically
> > >  > > need to
> > >  > >  > > solve a system of linear inequalities to
obtain a starting point.
> > >  > >  Have
> > >  > >  > you
> > >  > >  > > considered using linear programming? Either
simplex() in the
> > > "boot"
> > >  > >  > package
> > >  > >  > > or solveLP() in "linprog" would
work.  It seems to me that you
> > >  > > could use
> > >  > >  > any
> > >  > >  > > linear objective function in solveLP to
obtain a feasible
> > >  > > starting point.
> > >  > >  > > This is not the most efficient solution,
but it might be
> > > worth a
> > >  > > try.
> > >  > >  > >
> > >  > >  > > I am aware of other methods for generating
n-tuples that satisfy
> > >  > > linear
> > >  > >  > > inequality constraints, but AFAIK those are
not available in
> > > R.
> > >  > >  >
> > >  > >  > Thanks, Ravi. I had already conceived the
solution that you suggest,
> > >  > >  > actually using "lpSolve". I am able to
get a solution for my problem
> > >  > >  > with constrOptim, but I am not enough confident
that the
> > > solution is
> > >  > >  > right. That is why I am trying to get a solution
with rgenoud,
> > > but
> > >  > >  > unsuccessfully until now.
> > >  > >  >
> > >  > >  > Paul
> > >  > >  >
> > >  > >  >
> > >  > >  >
> > >  > >  > > -----Original Message-----
> > >  > >  > > From: r-help-bounces at stat.math.ethz.ch
> > >  > >  > > [ On Behalf Of Paul Smith
> > >  > >  > > Sent: Tuesday, July 03, 2007 4:10 PM
> > >  > >  > > To: R-help
> > >  > >  > > Subject: [R] Fine tunning rgenoud
> > >  > >  > >
> > >  > >  > > Dear All,
> > >  > >  > >
> > >  > >  > > I am trying to solve the following
maximization problem, but
> > > I cannot
> > >  > >  > > have rgenoud giving me a reliable solution.
> > >  > >  > >
> > >  > >  > > Any ideas?
> > >  > >  > >
> > >  > >  > > Thanks in advance,
> > >  > >  > >
> > >  > >  > > Paul
> > >  > >  > >
> > >  > >  > > ----------------------------
> > >  > >  > > library(rgenoud)
> > >  > >  > >
> > >  > >  > > v <- 0.90
> > >  > >  > > O1 <- 10
> > >  > >  > > O2 <- 20
> > >  > >  > > O0 <- v*O1+(1-v)*O2
> > >  > >  > >
> > >  > >  > > myfunc <- function(x) {
> > >  > >  > >   U0 <- x[1]
> > >  > >  > >   U1 <- x[2]
> > >  > >  > >   U2 <- x[3]
> > >  > >  > >   q0 <- x[4]
> > >  > >  > >   q1 <- x[5]
> > >  > >  > >   q2 <- x[6]
> > >  > >  > >   p <- x[7]
> > >  > >  > >
> > >  > >  > >   if (U0 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if (U1 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if (U2 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if ((U0-(U1+(O1-O0)*q1)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if ((U0-(U2+(O2-O0)*q2)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if ((U1-(U0+(O0-O1)*q0)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if ((U1-(U2+(O2-O1)*q2)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if((U2-(U0+(O0-O2)*q0)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if((U2-(U1+(O1-O2)*q1)) < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if(p < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if(p > 1)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if(q0 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if(q1 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else if(q2 < 0)
> > >  > >  > >     return(-1e+200)
> > >  > >  > >   else
> > >  > >  > >
> > >  > >  >
return(p*(sqrt(q0)-(O0*q0+U0))+(1-p)*(v*(sqrt(q1)-(O1*q1+U1))+(1-v)*(sqrt(q2
> > >  > >  > > )-(O2*q2+U2))))
> > >  > >  > >
> > >  > >  > > }
> > >  > >  > >
> > >  > >  >
genoud(myfunc,nvars=7,max=T,pop.size=6000,starting.values=runif(7),wait.gene
> > >  > >  > >
rations=150,max.generations=300,boundary.enforcement=2)
> > >  > >  > >
> > >  > >  > >
______________________________________________
> > >  > >  > > R-help at stat.math.ethz.ch mailing list
> > >  > >  > >
> > >  > >  > > PLEASE do read the posting guide
> > >  > >  >
> > >  > >  > > and provide commented, minimal,
self-contained, reproducible
> > > code.
> > >  > >  > >
> > >  > >  >
> > >  > >  > ______________________________________________
> > >  > >  > R-help at stat.math.ethz.ch mailing list
> > >  > >  >
> > >  > >  > PLEASE do read the posting guide
> > >  > >  > and provide commented, minimal, self-contained,
reproducible code.
> > >  > >  >
> > >  > >
> > >  > >  ______________________________________________
> > >  > >  R-help at stat.math.ethz.ch mailing list
> > >  > >
> > >  > >  PLEASE do read the posting guide
> > >  > >  and provide commented, minimal, self-contained,
reproducible code.
> > >  >
> > >  >
> > >
> > >  ______________________________________________
> > >  R-help at stat.math.ethz.ch mailing list
> > >
> > >  PLEASE do read the posting guide
> > >  and provide commented, minimal, self-contained, reproducible
code.
> >
>

R help - Jul 2007 - Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud

[R] Fine tunning rgenoud