🚀 go-pugleaf

Sorry, somehow my reply got posted to the wrong query.
_____________________

Perhaps I can be of some help since I developed the code.  It might be
of use to the general community if you would post all your replies.

In article <1992Dec18.193249.22059@murdoch.acc.Virginia.EDU> you write:
>Hi,
>
>  I am thinking about using VFSR (A Simulated Reannealing code from
>  NETLIB) on my problem which is to minimize a nonlinear function
>  subject to nonlinear inequality constraints. In addition, the
>  constraints are nondifferentiable wrt the parameters although
>  the objective function is differentiable.
>
>  I dont know anything about the theory behind VFSR and I wanted to
>  use it as a black box. My question is:
>  Can I use VFSR for this purpose? 

I've used similar constraints.  One case that was published was in
%A L. Ingber
%T Statistical mechanics of neocortical interactions:
A scaling paradigm applied to electroencephalography
%J Phys. Rev. A
%N 6
%V 44
%P 4017-4060
%D 1991

>  It is my understanding that VFSR requires the user to supply a
>  subroutine which returns with the cost fuction and a flag which
>  determines whether the (parameter) state at that point violates some
>  constraints or not. Apparently, if the constraints are violated, a
>  new set of trial parameters are generated. Is there a guarantee that
>  the new set of trial parameters are valid? If not, then it would seem
>  to me that you could get stuck at such points.

Yes, you could get stuck if the space being sampled had no other
good points.  I.e., on return from the cost function with an invalid
flag, a new random point is selected.  If you think your space might
be flooded with invalid points, you might set up some adaptive
schedule to change the ranges during the run.  I have done this
in other problems, e.g., by passing the parameter maximum and
minimum values along with the cost function.  On lines 133-135
in vfsr.h I have placed some comment for this possibility.

>  I would appreciate any information on the issues above.
>  Thanks.
>
>
>  -sriram srinivasan
>   (ss4i@kelvin.seas.virginia.edu)

Article 6507 of sci.math.num-analysis:
Path: mimsy!ingber
From: ingber@umiacs.umd.edu (Lester Ingber)
Newsgroups: sci.math.num-analysis
Subject: Re: Nonlinear systems of equations
Message-ID: <62947@mimsy.umd.edu>
Date: 19 Dec 92 18:49:22 GMT
References: <92Dec17.174419.27750@acs.ucalgary.ca> <168C1EBFA.MTURELLA@cmsa.gmr.com>
Sender: news@mimsy.umd.edu
Organization: UMIACS, University of Maryland, College Park, MD 20742
Lines: 57


Perhaps I can be of some help since I developed the code.  It might be
of use to the general community if you would post all your replies.

In article <1992Dec18.193249.22059@murdoch.acc.Virginia.EDU> you write:
>Hi,
>
>  I am thinking about using VFSR (A Simulated Reannealing code from
>  NETLIB) on my problem which is to minimize a nonlinear function
>  subject to nonlinear inequality constraints. In addition, the
>  constraints are nondifferentiable wrt the parameters although
>  the objective function is differentiable.
>
>  I dont know anything about the theory behind VFSR and I wanted to
>  use it as a black box. My question is:
>  Can I use VFSR for this purpose? 

I've used similar constraints.  One case that was published was in
%A L. Ingber
%T Statistical mechanics of neocortical interactions:
A scaling paradigm applied to electroencephalography
%J Phys. Rev. A
%N 6
%V 44
%P 4017-4060
%D 1991

>  It is my understanding that VFSR requires the user to supply a
>  subroutine which returns with the cost fuction and a flag which
>  determines whether the (parameter) state at that point violates some
>  constraints or not. Apparently, if the constraints are violated, a
>  new set of trial parameters are generated. Is there a guarantee that
>  the new set of trial parameters are valid? If not, then it would seem
>  to me that you could get stuck at such points.

Yes, you could get stuck if the space being sampled had no other
good points.  I.e., on return from the cost function with an invalid
flag, a new random point is selected.  If you think your space might be
flooded with invalid points, you might set up some adaptive schedule to
change the ranges during the run.  I have done this in other problems,
e.g., by passing the parameter maximum and minimum values along with
the cost function.  On lines 133-135 in vfsr.h I have placed some
comment for this possibility.

>  I would appreciate any information on the issues above.
>  Thanks.
>
>
>  -sriram srinivasan
>   (ss4i@kelvin.seas.virginia.edu)

Lester
-- 
|| Prof. Lester Ingber                         [10ATT]0-700-L-INGBER ||
|| Lester Ingber Research                        Fax: 0-700-4-INGBER ||
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