multiprocessing population generation, crossover and mutation

[Mauro Baluda]

If I'm correct, deap only parallelizes the fitness evaluation...
I think it would be useful to also parallelize the population generation, crossover and mutation

has any work been planned in this respect?
I would not like to duplicate the effort...

Mauro

[François-Michel De Rainville]

You are correct, the complete algorithms don't parallelize the generation, mutation, crossover, and selection step. This choice has been made to simplfy the code of the ea* algorithms and because these steps usually don't require much computing power compared to the evaluation. However, if you wish to add this level of parallelism you can of course build your own algorithm with the predefined tools.

Note that it would be nice to have an fully parallel example in the example folder. If you come up with a such an example using a standard problem (onemax or tsp, for example) we will be glad to review your pull request to the github main repo.

Cheers,

François-Michel

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