Re: Crossover operator for a superposed individual set

On Wed, 19 Nov 2003 20:56:52 +0100, "José Gomila Fàbregues"
<[EMAIL PROTECTED]> wrote:

>Hello,
>
>I'm a telecommunication science student, and I am working with GA. We have
>to optimitze a very hard problem. Our goal is to find a solution that is
>formed by a superposed set of individuals. That is, individuals that are
>forming our population are a set of parametres that are repeated because are
>superposed. An example:
>an simple individual can be formed by 4 parameters: X,Y,Z, (for spatial
>position) and V (a value in that position), or a superposed set of those
>parametres. We want to find an hipotetical composed individual formed by a 4
>simple individuals that are representated by
>        X1,Y1,Z1,V1
>        X2,Y2,Z2,V2
>        X3,Y3,Z3,V3
>        X4,Y4,Z4,V4
>The individual are formed by 4x4 parameters now.
>How can i write a good code to implement the crossover operator? Some body
>have an idea? May be a correlation between paramters can be a good option,
>but in the first generations there is not correlations.
>We work now with one point classical crossover operator and we have som
>goods solutions, but can it be optimitzed?
>Thank  you.
>
       Will your solution be a weighted sum of several individuals?
E.g., A{x1,y1,z1,v1} + B{x2,y2,z2,v2} + ...?  

      It is important to think about what aspects of a trial solution
should survive crossover in order to ensure that the result a) is a
valid trial solution and b) has a reasonable likelihood of retaining
the aspects of the trial solution that give it a high enough fitness
to be participating in creating the next generation of trial
solutions.  For example,  should crossover just involve exchange of a
subset of the individuals in each of two sets?  Or can it involve
exchange of, say the z coordinates from one subset with the z
coordinates of a corresponding subset of another set?  
      One of the sample problems given with the Generator download
http://www.nli-ltd.com/products/genetic_algorithms/demos.htm, "Wasps",
looks for the optimum way to distribute several "bug bombs" in order
to kill the largest number of wasps whose nests are distributed over a
region.  A trial solution is the set of coordinates of all the "bug
bombs".  As it turns out, in that particular problem a very simple
two-point crossover operator works fine.  
      However, the best crossover and mutation operators for any
particular problem depend strongly on the internal structure of the
problem.

SPM