Add initial specimen

[mparigi]

Is there a way to include a few individuals (likely good solutions, starting points) to the initial population, while leaving the rest of them random?

[koritsky]

I would also like that

[rayliuca]

Until the pull request get merged, you can try something like

def create_individual(seed_data):
    """ Create a candidate solution representation
        e.g. for a bit array representation:
    """
    if len(seed_data['starting points']) > 0:
        print('Got individual from data')
        return seed_data['starting points'].pop(0)
    
    print('Gen new individual')
    return [random.randint(0, 1) for _ in range(len(seed_data['genes_num']))]

ga = pyeasyga.GeneticAlgorithm({'starting points':[[1, 0],[0, 0]], 
                                'genes_num': 2},  # Input seed data
                                #some other parameters 
                                )

ga.create_individual = create_individual

## the reset of the implementation

ga.run()