def main(): configuration = Configuration() configuration.setPopulationSize(50) crossoverOp = CrossoverMutateOperator() configuration.addGeneticOperator(crossoverOp) chromosoneSel = BestChromosonesSelector() configuration.addNaturalSelector(chromosoneSel) geno = Genotype(configuration) for i in range(0,2*geno.getPopulation().getPopulationSize()): tspChromosone = TSPChromosone(distanceMap) tspChromosone.setRandomValue() geno.getPopulation().addChromosone(tspChromosone) for i in range(0,10): geno.evolve() geno.getPopulation().getChromosones().sort() print geno.getPopulation().getChromosones()[0]
def main(): configuration = Configuration() configuration.setPopulationSize(50) crossoverOp = CrossoverMutateOperator() configuration.addGeneticOperator(crossoverOp) chromosoneSel = BestChromosonesSelector() configuration.addNaturalSelector(chromosoneSel) geno = Genotype(configuration) for i in range(0, 2 * geno.getPopulation().getPopulationSize()): cubicSolverChromosone = CubicSolverChromosone(a, b, c, d) cubicSolverChromosone.setGeneBounds(-10.0, 10.0) cubicSolverChromosone.setRandomValue() geno.getPopulation().addChromosone(cubicSolverChromosone) for i in range(0, 1000): geno.evolve() geno.getPopulation().getChromosones().sort() print geno.getPopulation().getChromosones()[0]
def main(): configuration = Configuration() configuration.setPopulationSize(50) crossoverOp = CrossoverMutateOperator() configuration.addGeneticOperator(crossoverOp) chromosoneSel = BestChromosonesSelector() configuration.addNaturalSelector(chromosoneSel) geno = Genotype(configuration) for i in range(0,2*geno.getPopulation().getPopulationSize()): cubicSolverChromosone = CubicSolverChromosone(a,b,c,d) cubicSolverChromosone.setGeneBounds(-10.0,10.0) cubicSolverChromosone.setRandomValue() geno.getPopulation().addChromosone(cubicSolverChromosone) for i in range(0,1000): geno.evolve() geno.getPopulation().getChromosones().sort() print geno.getPopulation().getChromosones()[0]