- Hi Hazem,

You may also try our Big-Bang big-Crunh method for finding the optimum

parameter

set of a given function.

This method converges to global optimum 1000+ faster than Genetic Algorithms.

You may download the MATLAB codes at my web site at:

www3.itu.edu.tr/~okerol

The principle is: Like GA, the algorithm chooses randomly a number of possible

choices (chromosomes in GA) calculates their cost function then chooses the

minimum of them. Then by using normal probability distribution generates new

candidates around that point.

Hi Thomas,

You may also use that method for Genetic Programming "after" obtaining a

structure, to find the constants that may appear in that S-expression. That

speeds the Genetic search procedure.

Kind Regards,

Osman

Quoting Thomas Weise <tweise@...>:

> Hello Hazem.

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

>

>

>

> Hm, if you want to find minima or maxima of a _given_ function,

>

> Genetic Programming may not be the approach of choice.

>

> Here, other methods like Evolution Strategy/Differential Evolution

>

> or Particle Swarm Optimization may be better.

>

> Example: f(x)=x*x-3x -> Find the minimum of this function.

>

> Answer (by PSO): Minimum f(x)=-2.25 is at x=1.5

>

>

>

> With Genetic Programming we normally breed tree-shaped structure.

>

> Since mathematical functions are in principle hierarchies of

>

> mathematical expressions which can in turn be expressed as trees,

>

> GP is a good means to _find_ functions that fit to given sample

>

> data.

>

> Example: A set of values (x,f(x)) is given like {(0,0); (1,-2); (2,-2).

>

> -> Find the function f(x) that fits to these data samples.

>

> -> Answer (by GP): f(x)=x*x-3x

>

>

>

> I have tried to compile a summary on different evolutionary

>

> algorithms. Maybe it can be helpful for you. You can find it at

>

> http://www.it-weise.de/projects/book.pdf

>

>

>

> Kind regards,

>

> Thomas.

>

>

>

> From: genetic_programming@yahoogroups.com

> [mailto:genetic_programming@yahoogroups.com] On Behalf Of Hazem Saleh

> Sent: Tuesday, December 25, 2007 5:12 AM

> To: genetic_programming@yahoogroups.com

> Subject: [GP] A question about Genetic Programming

>

>

>

> Hi Guys;

> Iam a beginner at the genetic programming.

> I have a question which may be a stupid one.

> Can I use genetic programming for function (with several independent

> variables) optimization like genetic algorithms?

> If the answer is yes; Is there a specific tutorial that can help me to

> realize how this can be done.

> Iam sorry again if my question is stupid; Iam a beginner.

> Thanks all!

>

>

>

>

>

> [Non-text portions of this message have been removed]

>

>

This message was sent using IMP, the Internet Messaging Program. - Hello,

i's a good idea to use GP for independant variable but i haven't try

it but i think that it can be possible. if you find any think about

this you can write me perhaps i can help in th efitness function.

thank's

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

This message was sent using IMP, the Internet Messaging Program. - Does anyone know of an online source for this article? I have not been able

to track it down.

Thanks,

David vun Kannon

@inproceedings{DBLP:conf/icga/Paredis95,

author = {Jan Paredis},

title = {The Symbiotic Evolution of Solutions and Their

Representations},

booktitle = {ICGA},

year = {1995},

pages = {359-365},

crossref = {DBLP:conf/icga/1995},

bibsource = {DBLP, http://dblp.uni-trier.de}

}