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Date: Wed, 13 Jan 2010 17:44:25 -0600
Message-ID: <3c682ecd1001131544x43180d70i1992a0ab237dd8f1@mail.gmail.com>
Subject: Re: SCALING GENETIC ALGORITHMS USING MAPREDUCE
From: Abhishek Verma <vermaabhishekp@gmail.com>
To: general@hadoop.apache.org
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Hi Alberto,

The paper considers only selecto-recombinative genetic algorithms as
mentioned in Section III.A. The mutation operators could be done on the
reduce  after the crossover or before it as required. Elitism can be
implemented by emitting the individual with a different value in the map and
then directly writing it to context in the reduce.

If you are up for it, we could collaborate together to work on your problem.

Hope this helps.
-Abhishek.

On Wed, Jan 13, 2010 at 5:36 PM, Alberto Luengo Cabanillas <
cabiwan@gmail.com> wrote:

> Hi everyone! For the last six months. my work with Hadoop is being focused
> in developing a stable MRPGA. Last paper I read ("Scaling Genetic
> Algorithms
> Using MapReduce") was a fantastic job and gave me a bunch of ideas; but I
> have some questions relative to this paper and I think they may be useful
> for community:
>
> Anywhere in the paper talks about elitism rate nor mutation rate. It only
> talks about selection and crossover. In fact, this part (page 3 and so)
> talks about an INDIVIDUALREPRESENTATION(key) function, which I suppose is
> used to represent the key part of the par (i.e., if it is Text, its
> representation is a String). Also there are TOURN(tournArray) (?) and
> CROSSOVER(crossArray), which I think is related to mutation.
>
> How it is supposed to be implemented the mutation part in the process?.
> Have
> you considered some kind of elitism rate for chossing population?.
>
> Thanks a lot in advance.
>
>
> --
> Alberto
>

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