public static void main(final String[] args) throws IOException { final String base = "/home/fwilhelm/Workspace/Development/Projects/" + "Jenetics/jenetics.tool/src/main/resources/io/jenetics/tool/moea"; final Path data = Paths.get(base, "circle_min_front.dat"); final Path output = Paths.get(base, "circle_min_front.svg"); final Engine<DoubleGene, Vec<double[]>> engine = Engine.builder(PROBLEM) .alterers( new Mutator<>(0.1), new MeanAlterer<>()) .offspringSelector(new TournamentSelector<>(3)) .survivorsSelector(UFTournamentSelector.ofVec()) .minimizing() .build(); final ISeq<Phenotype<DoubleGene, Vec<double[]>>> front = engine.stream() .limit(Limits.byFixedGeneration(100)) .collect(MOEA.toParetoSet(IntRange.of(100, 150))); final StringBuilder out = new StringBuilder(); out.append("#x y\n"); front.forEach(p -> { out.append(p.getFitness().data()[0]); out.append(" "); out.append(p.getFitness().data()[1]); out.append("\n"); }); Files.write(data, out.toString().getBytes()); final Gnuplot gnuplot = new Gnuplot(Paths.get(base, "circle_points.gp")); gnuplot.create(data, output); }
public static void main(final String[] args) { final Engine<ProgramGene<Double>, Double> engine = Engine .builder(SymbolicRegression::error, CODEC) .minimizing() .alterers( new SingleNodeCrossover<>(), new Mutator<>()) .build(); final ProgramGene<Double> program = engine.stream() .limit(100) .collect(EvolutionResult.toBestGenotype()) .getGene(); System.out.println(program.toParenthesesString()); }
.offspringSelector(new TournamentSelector<>(2)) .survivorsSelector(UFTournamentSelector.ofVec()) .minimizing() .build();
public static void main(final String[] args) { final Problem<double[], DoubleGene, Double> problem = Problem.of( v -> Math.sin(v[0])*Math.cos(v[1]), Codecs.ofVector(DoubleRange.of(0, 2*Math.PI), 2) ); final Engine<DoubleGene, Double> engine1 = Engine.builder(problem) .minimizing() .alterers(new Mutator<>(0.2)) .selector(new MonteCarloSelector<>()) .build(); final Engine<DoubleGene, Double> engine2 = Engine.builder(problem) .minimizing() .alterers( new Mutator<>(0.1), new MeanAlterer<>()) .selector(new RouletteWheelSelector<>()) .build(); final Genotype<DoubleGene> result = ConcatEngine.of( engine1.limit(50), engine2.limit(() -> Limits.bySteadyFitness(30))) .stream() .collect(EvolutionResult.toBestGenotype()); System.out.println(result + ": " + problem.fitness().apply(problem.codec().decode(result))); }
public static void main(final String[] args) { final Problem<double[], DoubleGene, Double> problem = Problem.of( v -> Math.sin(v[0])*Math.cos(v[1]), Codecs.ofVector(DoubleRange.of(0, 2*Math.PI), 2) ); final Engine<DoubleGene, Double> engine1 = Engine.builder(problem) .minimizing() .alterers(new Mutator<>(0.2)) .selector(new MonteCarloSelector<>()) .build(); final Engine<DoubleGene, Double> engine2 = Engine.builder(problem) .minimizing() .alterers( new Mutator<>(0.1), new MeanAlterer<>()) .selector(new RouletteWheelSelector<>()) .build(); final Genotype<DoubleGene> result = CyclicEngine.of( engine1.limit(50), engine2.limit(() -> Limits.bySteadyFitness(30))) .stream() .limit(Limits.bySteadyFitness(1000)) .collect(EvolutionResult.toBestGenotype()); System.out.println(result + ": " + problem.fitness().apply(problem.codec().decode(result))); }
@Test public void variableDoubleSum() { final Problem<int[], IntegerGene, Integer> problem = Problem.of( array -> IntStream.of(array).sum(), Codec.of( Genotype.of(IntegerChromosome.of(0, 100, IntRange.of(10, 100))), gt -> gt.getChromosome().as(IntegerChromosome.class).toArray() ) ); final Engine<IntegerGene, Integer> engine = Engine.builder(problem) .alterers( new Mutator<>(), new SwapMutator<>()) .selector(new TournamentSelector<>()) .minimizing() .build(); final int[] result = problem.codec().decode( engine.stream() .limit(100) .collect(EvolutionResult.toBestGenotype()) ); Assert.assertTrue(result.length < 50, "result length: " + result.length); //System.out.println(result.length); //System.out.println(Arrays.toString(result)); }
public static void main(final String[] args) { final Engine<ProgramGene<Double>, Double> engine = Engine .builder(Example::error, CODEC) .minimizing() .alterers( new SingleNodeCrossover<>(), new Mutator<>()) .build(); final ProgramGene<Double> program = engine.stream() .limit(3000) .collect(EvolutionResult.toBestGenotype()) .getGene(); System.out.println(Tree.toString(program)); for (int i = 0; i < SAMPLES.length; ++i) { final double x = SAMPLES[i][0]; final double result = program.eval(x); System.out.println(format( "%2.2f: %2.4f, %2.4f: %2.5f", x, f(x), result, abs(f(x) - result) )); } }
public static void main(final String[] args) { final Problem<double[], DoubleGene, Double> problem = Problem.of( v -> Math.sin(v[0])*Math.cos(v[1]), Codecs.ofVector(DoubleRange.of(0, 2*Math.PI), 2) ); final Engine.Builder<DoubleGene, Double> builder = Engine .builder(problem) .minimizing(); final Genotype<DoubleGene> result = AdaptiveEngine.<DoubleGene, Double>of(er -> engine(er, builder)) .stream() .limit(Limits.bySteadyFitness(50)) .collect(EvolutionResult.toBestGenotype()); System.out.println(result + ": " + problem.fitness().apply(problem.codec().decode(result))); }
public static void main(final String[] args) { final SubsetSum problem = of(500, 15, new LCG64ShiftRandom(101010)); final Engine<EnumGene<Integer>, Integer> engine = Engine.builder(problem) .minimizing() .maximalPhenotypeAge(5) .alterers( new PartiallyMatchedCrossover<>(0.4), new Mutator<>(0.3)) .build(); final Phenotype<EnumGene<Integer>, Integer> result = engine.stream() .limit(Limits.bySteadyFitness(55)) .collect(EvolutionResult.toBestPhenotype()); System.out.print(result); }