[Tutor] My shot at the partitioning problem

[Danny Yoo]

On Sat, 18 Aug 2001, Roeland Rengelink wrote:

> One note on your code. You have:
> 
> def stringCrossover(s1, s2, probability=0.5):
>     """A simple crossover operator on strings s1 and s2."""
>     for i in range(len(s1)):
>         if random.random() < probability:
>             return s1[:i] + s2[i:]
>     return s1
> 
> ie.
> 
> 50 % s1[:0]+s2[0:]
> 25 % s1[:1]+s2[1:]
> 12.5% s1[:2]+s2[2:]
> etc.
> 
> Is that really what you want?

Oh no!  You're right: As it's written, the crossover function is biased
towards crossing string over near the beginning of the string!  That's
definitely not what I had in mind: it would be better if it could cross
over anywhere with equal probability.



> I thought more something like:
> 
> def stringCrossover(s1, s2):
>     """A simple crossover operator on strings s1 and s2."""
>     i = random.randrange(len(s1))
>     return s1[:i]+s2[i:]

Yes, your version of stringCrossover makes much more sense.  I believe I
was writing the string mutating function at the same time as
stringCrossover(), and had gotten those two functions confused in my head.  

I'll make this correction and see if it improves the search, although from
your analysis, this still sounds like a dead end.  I must admit that I've
just started reading an introductory text on genetic algorithms; I have a
lot of reading to do.

Thanks again!