PyGA/test.py at master · sjhwang410/PyGA · GitHub

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from time import time, sleep

from ga.ga import GeneticAlgorithm
from ga.chromosome import Chromosome

def fitness(data):
    limit = 15
    items = {0: [10, 2], 1: [5, 5], 2: [1, 1], 3: [3, 2], 4: [4, 5], 5: [3, 3]}
    sleep(0.001)
    val = 0.0
    vol = 0.0
    for i in range(len(data)):
        if data[i]:
            val += items[i][1]
            vol += items[i][0]

    if vol > limit:
        return 0

    return val

if __name__ == '__main__':
    # set chromosome shape
    chromosome = Chromosome()
    chromosome.add_gene('choice', [0, 1])
    chromosome.add_gene('choice', [0, 1])
    chromosome.add_gene('choice', [0, 1])
    chromosome.add_gene('choice', [0, 1])
    chromosome.add_gene('choice', [0, 1])
    chromosome.add_gene('choice', [0, 1])

    # make object for genetic algorithm
    genetic = GeneticAlgorithm(fitness, 50, chromosome, 50, thread_count=3)
    print(genetic.help)
    # set operation using genetic algorithm
    genetic.add_method('selection', 'roulette')
    genetic.add_method('crossover', 'one_point')
    genetic.add_method('mutation', 'elitist')
    genetic.add_method('survivor', 'elitist')

    # learning
    t = time()
    genetic.run()

    print((time() - t) / 60)
    print(genetic.population[0])