/*
 * Java Genetic Algorithm Library (jenetics-9.1.0).
 * Copyright (c) 2007-2026 Franz Wilhelmstötter
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * Author:
 *    Franz Wilhelmstötter (franz.wilhelmstoetter@gmail.com)
 */
package io.jenetics.engine;

import static java.lang.String.format;
import static java.util.Objects.requireNonNull;
import static java.util.concurrent.CompletableFuture.supplyAsync;
import static java.util.concurrent.ForkJoinPool.commonPool;

import java.time.InstantSource;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.Executor;
import java.util.concurrent.ForkJoinPool;
import java.util.function.Function;
import java.util.function.Supplier;
import java.util.stream.Stream;

import io.jenetics.Alterer;
import io.jenetics.AltererResult;
import io.jenetics.Chromosome;
import io.jenetics.Gene;
import io.jenetics.Genotype;
import io.jenetics.Optimize;
import io.jenetics.Phenotype;
import io.jenetics.Selector;
import io.jenetics.util.BatchExecutor;
import io.jenetics.util.Copyable;
import io.jenetics.util.Factory;
import io.jenetics.util.ISeq;
import io.jenetics.util.MSeq;
import io.jenetics.util.NanoClock;
import io.jenetics.util.Seq;

/**
 * Genetic algorithm <em>engine</em> which is the main class. The following
 * example shows the main steps in initializing and executing the GA.
 * {@snippet lang="java":
 * public class RealFunction {
 *    // Definition of the fitness function.
 *    private static Double eval(final Genotype<DoubleGene> gt) {
 *        final double x = gt.gene().doubleValue();
 *        return cos(0.5 + sin(x))*cos(x);
 *    }
 *
 *    void main() {
 *        // Create/configuring the engine via its builder.
 *        final Engine<DoubleGene, Double> engine = Engine
 *            .builder(
 *                RealFunction::eval,
 *                DoubleChromosome.of(0.0, 2.0*PI))
 *            .populationSize(500)
 *            .optimize(Optimize.MINIMUM)
 *            .alterers(
 *                new Mutator<>(0.03),
 *                new MeanAlterer<>(0.6))
 *            .build();
 *
 *        // Execute the GA (engine).
 *        final Phenotype<DoubleGene, Double> result = engine.stream()
 *             // Truncate the evolution stream if no better individual could
 *             // be found after 5 consecutive generations.
 *            .limit(bySteadyFitness(5))
 *             // Terminate the evolution after maximal 100 generations.
 *            .limit(100)
 *            .collect(toBestPhenotype());
 *     }
 * }
 * }
 *
 * The architecture allows to decouple the configuration of the engine from the
 * execution. The {@code Engine} is configured via the {@code Engine.Builder}
 * class and can't be changed after creation. The actual <i>evolution</i> is
 * performed by the {@link EvolutionStream}, which is created by the
 * {@code Engine}.
 *
 * <H2>Concurrency</H2>
 * By default, the engine uses the {@link ForkJoinPool#commonPool()} for
 * executing the evolution steps and evaluating the fitness function concurrently.
 * You can change the used execution services with the {@link Builder#executor(Executor)}
 * method. If you want to use a different executor for evaluating the fitness
 * functions, you have to set the {@link Builder#fitnessExecutor(BatchExecutor)}.
 *
 * {@snippet lang="java":
 * final Engine<DoubleGene, Double> engine = Engine
 *     .builder(null) // @replace substring='null' replacement="..."
 *     // Using this execution service for parallelize the evolution steps.
 *     .executor(Executors.newFixedThreadPool(5))
 *     // Using one virtual thread for every fitness function evaluation.
 *     .fitnessExecutor(BatchExecutor.ofVirtualThreads())
 *     .build();
 * }
 *
 * @implNote
 *     This class is thread safe: The engine maintains no mutable state.
 *     Therefore, it is safe to create multiple evolution streams with one
 *     engine, which may be actually used in different threads.
 *
 * @see Engine.Builder
 * @see EvolutionStart
 * @see EvolutionResult
 * @see EvolutionStream
 * @see EvolutionStatistics
 * @see Codec
 * @see Constraint
 *
 * @param <G> the gene type
 * @param <C> the fitness result type
 *
 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
 * @since 3.0
 * @version 7.0
 */
public final class Engine<
        G extends Gene<?, G>,
        C extends Comparable<? super C>
>
        implements
                Evolution<G, C>,
                EvolutionStreamable<G, C>,
                Evaluator<G, C>
{

        // Problem definition.
        private final Evaluator<G, C> _evaluator;
        private final Factory<Genotype<G>> _genotypeFactory;
        private final Constraint<G, C> _constraint;
        private final Optimize _optimize;

        // Evolution parameters.
        private final EvolutionParams<G, C> _evolutionParams;

        // Execution context for concurrent execution of evolving steps.
        private final Executor _executor;
        private final InstantSource _clock;
        private final EvolutionInterceptor<G, C> _interceptor;


        /**
         * Create a new GA engine with the given parameters.
         *
         * @param evaluator the population fitness evaluator
         * @param genotypeFactory the genotype factory this GA is working with.
         * @param constraint phenotype constraint which can override the default
         *        implementation the {@link Phenotype#isValid()} method and repairs
         *        invalid phenotypes when needed.
         * @param optimize the kind of optimization (minimize or maximize)
         * @param evolutionParams the evolution parameters, which influences the
         *        evolution process
         * @param executor the executor used for executing the single evolved steps
         * @param clock the clock used for calculating the timing results
         * @param interceptor the evolution interceptor, which gives additional
         *        possibilities to influence the actual evolution
         * @throws NullPointerException if one of the arguments is {@code null}
         */
        Engine(
                final Evaluator<G, C> evaluator,
                final Factory<Genotype<G>> genotypeFactory,
                final Constraint<G, C> constraint,
                final Optimize optimize,
                final EvolutionParams<G, C> evolutionParams,
                final Executor executor,
                final InstantSource clock,
                final EvolutionInterceptor<G, C> interceptor
        ) {
                _evaluator = requireNonNull(evaluator);
                _genotypeFactory = requireNonNull(genotypeFactory);
                _constraint = requireNonNull(constraint);
                _optimize = requireNonNull(optimize);
                _evolutionParams = requireNonNull(evolutionParams);
                _executor = requireNonNull(executor);
                _clock = requireNonNull(clock);
                _interceptor = requireNonNull(interceptor);
        }

        @Override
        public EvolutionResult<G, C> evolve(final EvolutionStart<G, C> start) {
                final EvolutionTiming timing = new EvolutionTiming(_clock);
                timing.evolve.start();

                final EvolutionStart<G, C> interceptedStart = _interceptor.before(start);

                // Create an initial population if `start` is empty.
                final EvolutionStart<G, C> es = interceptedStart.population().isEmpty()
                        ? evolutionStart(interceptedStart)
                        : interceptedStart;

                // Initial evaluation of the population.
                final ISeq<Phenotype<G, C>> population = es.isDirty()
                        ? timing.evaluation.timing(() -> eval(es.population()))
                        : es.population();

                // Select the offspring population.
                final CompletableFuture<ISeq<Phenotype<G, C>>> offspring =
                        supplyAsync(() ->
                                timing.offspringSelection.timing(() ->
                                        selectOffspring(population)
                                ),
                                _executor
                        );

                // Select the survivor population.
                final CompletableFuture<ISeq<Phenotype<G, C>>> survivors =
                        supplyAsync(() ->
                                timing.survivorsSelection.timing(() ->
                                        selectSurvivors(population)
                                ),
                                _executor
                        );

                // Altering the offspring population.
                final CompletableFuture<AltererResult<G, C>> alteredOffspring =
                        offspring.thenApplyAsync(off ->
                                timing.offspringAlter.timing(() ->
                                        _evolutionParams.alterer().alter(off, es.generation())
                                ),
                                _executor
                        );

                // Filter and replace invalid and old survivor individuals.
                final CompletableFuture<FilterResult<G, C>> filteredSurvivors =
                        survivors.thenApplyAsync(sur ->
                                timing.survivorFilter.timing(() ->
                                        filter(sur, es.generation())
                                ),
                                _executor
                        );

                // Filter and replace invalid and old offspring individuals.
                final CompletableFuture<FilterResult<G, C>> filteredOffspring =
                        alteredOffspring.thenApplyAsync(off ->
                                timing.offspringFilter.timing(() ->
                                        filter(off.population(), es.generation())
                                ),
                                _executor
                        );

                // Combining survivors and offspring to the new population.
                final CompletableFuture<ISeq<Phenotype<G, C>>> nextPopulation =
                        filteredSurvivors.thenCombineAsync(
                                filteredOffspring,
                                (s, o) -> ISeq.of(s.population().append(o.population())),
                                _executor
                        );

                // Evaluate the fitness-function and wait for a result.
                final ISeq<Phenotype<G, C>> pop = nextPopulation.join();
                final ISeq<Phenotype<G, C>> result = timing.evaluation.timing(() ->
                        eval(pop)
                );

                final int killCount =
                        filteredOffspring.join().killCount() +
                        filteredSurvivors.join().killCount();

                final int invalidCount =
                        filteredOffspring.join().invalidCount() +
                        filteredSurvivors.join().invalidCount();

                final int alterationCount = alteredOffspring.join().alterations();

                EvolutionResult<G, C> er = EvolutionResult.of(
                        _optimize,
                        result,
                        es.generation(),
                        timing.toDurations(),
                        killCount,
                        invalidCount,
                        alterationCount
                );

                final EvolutionResult<G, C> interceptedResult = _interceptor.after(er);
                if (er != interceptedResult) {
                        er = interceptedResult.withPopulation(
                                timing.evaluation.timing(() ->
                                        eval(interceptedResult.population())
                        ));
                }

                timing.evolve.stop();

                return er
                        .withDurations(timing.toDurations())
                        .clean();
        }

        // Selects the survivor population. A new population object is returned.
        private ISeq<Phenotype<G, C>>
        selectSurvivors(final ISeq<Phenotype<G, C>> population) {
                return _evolutionParams.survivorsSize() > 0
                        ? _evolutionParams.survivorsSelector()
                                .select(population, _evolutionParams.survivorsSize(), _optimize)
                        : ISeq.empty();
        }

        // Selects the offspring population. A new population object is returned.
        private ISeq<Phenotype<G, C>>
        selectOffspring(final ISeq<Phenotype<G, C>> population) {
                return _evolutionParams.offspringSize() > 0
                        ? _evolutionParams.offspringSelector()
                                .select(population, _evolutionParams.offspringSize(), _optimize)
                        : ISeq.empty();
        }

        // Filters out invalid and old individuals. Filtering is done in place.
        private FilterResult<G, C> filter(
                final Seq<Phenotype<G, C>> population,
                final long generation
        ) {
                int killCount = 0;
                int invalidCount = 0;

                final MSeq<Phenotype<G, C>> pop = MSeq.of(population);
                for (int i = 0, n = pop.size(); i < n; ++i) {
                        final Phenotype<G, C> individual = pop.get(i);

                        if (!_constraint.test(individual)) {
                                pop.set(i, _constraint.repair(individual, generation));
                                ++invalidCount;
                        } else if (individual.age(generation) >
                                                _evolutionParams.maximalPhenotypeAge())
                        {
                                pop.set(i, Phenotype.of(_genotypeFactory.newInstance(), generation));
                                ++killCount;
                        }
                }

                return new FilterResult<>(pop.toISeq(), killCount, invalidCount);
        }


        /* *************************************************************************
         * Evaluation methods.
         **************************************************************************/

        /**
         * Evaluates the fitness function of the given population with the configured
         * {@link Evaluator} of this engine and returns a new population
         * with its fitness value assigned.
         *
         * @since 5.0
         *
         * @see Evaluator
         * @see Evaluator#eval(Seq)
         *
         * @param population the population to evaluate
         * @return a new population with assigned fitness values
         * @throws IllegalStateException if the configured fitness function doesn't
         *         return a population with the same size as the input population.
         *         This exception is also thrown if one of the populations
         *         phenotype has no fitness value assigned.
         */
        @Override
        public ISeq<Phenotype<G, C>> eval(final Seq<Phenotype<G, C>> population) {
                final ISeq<Phenotype<G, C>> evaluated = _evaluator.eval(population);

                if (population.size() != evaluated.size()) {
                        throw new IllegalStateException(format(
                                "Expected %d individuals, but got %d. " +
                                        "Check your evaluator function.",
                                population.size(), evaluated.size()
                        ));
                }
                if (!evaluated.forAll(Phenotype::isEvaluated)) {
                        throw new IllegalStateException(
                                "Some phenotypes have no assigned fitness value. " +
                                        "Check your evaluator function."
                        );
                }

                return evaluated;
        }


        /* *************************************************************************
         * Evolution Stream creation.
         **************************************************************************/

        @Override
        public EvolutionStream<G, C>
        stream(final Supplier<EvolutionStart<G, C>> start) {
                return EvolutionStream.ofEvolution(
                        () -> evolutionStart(start.get()),
                        this
                );
        }

        @Override
        public EvolutionStream<G, C> stream(final EvolutionInit<G> init) {
                return stream(evolutionStart(init));
        }

        private EvolutionStart<G, C>
        evolutionStart(final EvolutionStart<G, C> start) {
                final ISeq<Phenotype<G, C>> population = start.population();
                final long gen = start.generation();

                final Stream<Phenotype<G, C>> stream = Stream.concat(
                        population.stream(),
                        _genotypeFactory.instances()
                                .map(gt -> Phenotype.of(gt, gen))
                );

                final ISeq<Phenotype<G, C>> pop = stream
                        .limit(populationSize())
                        .collect(ISeq.toISeq());

                return EvolutionStart.of(pop, gen);
        }

        private EvolutionStart<G, C>
        evolutionStart(final EvolutionInit<G> init) {
                final ISeq<Genotype<G>> pop = init.population();
                final long gen = init.generation();

                return evolutionStart(
                        EvolutionStart.of(
                                pop.map(gt -> Phenotype.of(gt, gen)),
                                gen
                        )
                );
        }

        /* *************************************************************************
         * Property access methods.
         **************************************************************************/

        /**
         * Return the used genotype {@link Factory} of the GA. The genotype factory
         * is used for creating the initial population and new, random individuals
         * when needed (as replacement for invalid and/or died genotypes).
         *
         * @return the used genotype {@link Factory} of the GA.
         */
        public Factory<Genotype<G>> genotypeFactory() {
                return _genotypeFactory;
        }

        /**
         * Return the constraint of the evolution problem.
         *
         * @since 5.0
         *
         * @return the constraint of the evolution problem
         */
        public Constraint<G, C> constraint() {
                return _constraint;
        }

        /**
         * Return the used survivor {@link Selector} of the GA.
         *
         * @return the used survivor {@link Selector} of the GA.
         */
        public Selector<G, C> survivorsSelector() {
                return _evolutionParams.survivorsSelector();
        }

        /**
         * Return the used offspring {@link Selector} of the GA.
         *
         * @return the used offspring {@link Selector} of the GA.
         */
        public Selector<G, C> offspringSelector() {
                return _evolutionParams.offspringSelector();
        }

        /**
         * Return the used {@link Alterer} of the GA.
         *
         * @return the used {@link Alterer} of the GA.
         */
        public Alterer<G, C> alterer() {
                return _evolutionParams.alterer();
        }

        /**
         * Return the number of selected offspring.
         *
         * @return the number of selected offspring
         */
        public int offspringSize() {
                return _evolutionParams.offspringSize();
        }

        /**
         * The number of selected survivors.
         *
         * @return the number of selected survivors
         */
        public int survivorsSize() {
                return _evolutionParams.survivorsSize();
        }

        /**
         * Return the number of individuals of a population.
         *
         * @return the number of individuals of a population
         */
        public int populationSize() {
                return _evolutionParams.populationSize();
        }

        /**
         * Return the maximal allowed phenotype age.
         *
         * @return the maximal allowed phenotype age
         */
        public long maximalPhenotypeAge() {
                return _evolutionParams.maximalPhenotypeAge();
        }

        /**
         * Return the optimization strategy.
         *
         * @return the optimization strategy
         */
        public Optimize optimize() {
                return _optimize;
        }

        /**
         * Return the {@link InstantSource} the engine is using for measuring the
         * execution time.
         *
         * @return the clock used for measuring the execution time
         */
        public InstantSource clock() {
                return _clock;
        }

        /**
         * Return the {@link Executor} the engine is using for executing the
         * evolution steps.
         *
         * @return the executor used for performing the evolution steps
         */
        public Executor executor() {
                return _executor;
        }

        /**
         * Return the evolution interceptor.
         *
         * @since 6.0
         *
         * @return the evolution result mapper
         */
        public EvolutionInterceptor<G, C> interceptor() {
                return _interceptor;
        }

        /**
         * Create a new evolution {@code Engine.Builder} initialized with the values
         * of the current evolution {@code Engine}. With this method, the evolution
         * engine can serve as a template for a new one.
         *
         * @apiNote
         * If this engine was created from a fitness function and a dedicated
         * fitness executor, the returned builder preserves the fitness function,
         * but not the originally configured fitness executor. Calling
         * {@link Builder#fitnessExecutor(BatchExecutor)} on the returned builder
         * creates a new fitness evaluator with the given executor.
         *
         * @return a new engine builder
         */
        public Builder<G, C> toBuilder() {
                return new Builder<>(_evaluator, _genotypeFactory)
                        .clock(_clock)
                        .executor(_executor)
                        .optimize(_optimize)
                        .constraint(_constraint)
                        .evolutionParams(_evolutionParams)
                        .interceptor(_interceptor);
        }


        /* *************************************************************************
         * Static Builder methods.
         **************************************************************************/

        /**
         * Create a new evolution {@code Engine.Builder} with the given fitness
         * function and genotype factory.
         *
         * @param ff the fitness function
         * @param gtf the genotype factory
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return a new engine builder
         * @throws java.lang.NullPointerException if one of the arguments is
         *         {@code null}.
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        Builder<G, C> builder(
                final Function<? super Genotype<G>, ? extends C> ff,
                final Factory<Genotype<G>> gtf
        ) {
                return new Builder<>(
                        new FitnessEvaluator<>(ff, BatchExecutor.of(commonPool())),
                        gtf
                );
        }

        /**
         * Create a new evolution {@code Engine.Builder} with the given fitness
         * function and problem {@code codec}.
         *
         * @since 3.2
         *
         * @param ff the fitness evaluator
         * @param codec the problem codec
         * @param <T> the fitness function input type
         * @param <C> the fitness function result type
         * @param <G> the gene type
         * @return a new engine builder
         * @throws java.lang.NullPointerException if one of the arguments is
         *         {@code null}.
         */
        public static <T, G extends Gene<?, G>, C extends Comparable<? super C>>
        Builder<G, C> builder(
                final Function<? super T, ? extends C> ff,
                final Codec<T, G> codec
        ) {
                return builder(ff.compose(codec.decoder()), codec.encoding());
        }

        /**
         * Create a new evolution {@code Engine.Builder} for the given
         * {@link Problem}.
         *
         * @since 3.4
         *
         * @param problem the problem to be solved by the evolution {@code Engine}
         * @param <T> the (<i>native</i>) argument type of the problem fitness function
         * @param <G> the gene type the evolution engine is working with
         * @param <C> the result type of the fitness function
         * @return Create a new evolution {@code Engine.Builder}
         */
        public static <T, G extends Gene<?, G>, C extends Comparable<? super C>>
        Builder<G, C> builder(final Problem<T, G, C> problem) {
                final var builder = builder(problem.fitness(), problem.codec());
                problem.constraint().ifPresent(builder::constraint);
                return builder;
        }

        /**
         * Create a new evolution {@code Engine.Builder} with the given fitness
         * function and chromosome templates.
         *
         * @param ff the fitness function
         * @param chromosome the first chromosome
         * @param chromosomes the chromosome templates
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return a new engine builder
         * @throws java.lang.NullPointerException if one of the arguments is
         *         {@code null}.
         */
        @SafeVarargs
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        Builder<G, C> builder(
                final Function<? super Genotype<G>, ? extends C> ff,
                final Chromosome<G> chromosome,
                final Chromosome<G>... chromosomes
        ) {
                return builder(ff, Genotype.of(chromosome, chromosomes));
        }


        /* *************************************************************************
         * Engine builder
         **************************************************************************/


        /**
         * Builder class for building GA {@code Engine} instances.
         *
         * @see Engine
         *
         * @param <G> the gene type
         * @param <C> the fitness function result type
         *
         * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
         * @since 3.0
         * @version 6.0
         */
        public static final class Builder<
                G extends Gene<?, G>,
                C extends Comparable<? super C>
        >
                implements Copyable<Builder<G, C>>
        {

                // No default values for this properties.
                private final Evaluator<G, C> _evaluator;
                private final Factory<Genotype<G>> _genotypeFactory;
                private Constraint<G, C> _constraint;
                private Optimize _optimize = Optimize.MAXIMUM;

                // Evolution parameters.
                private final EvolutionParams.Builder<G, C> _evolutionParams =
                        EvolutionParams.builder();


                // Engine execution environment.
                private Executor _executor = commonPool();
                private BatchExecutor _fitnessExecutor = null;
                private InstantSource _clock = NanoClock.systemUTC();

                private EvolutionInterceptor<G, C> _interceptor =
                        EvolutionInterceptor.identity();

                /**
                 * Create a new evolution {@code Engine.Builder} with the given fitness
                 * evaluator and genotype factory. This is the most general way of
                 * creating an engine builder.
                 *
                 * @since 5.0
                 *
                 * @see Engine#builder(Function, Codec)
                 * @see Engine#builder(Function, Factory)
                 * @see Engine#builder(Problem)
                 * @see Engine#builder(Function, Chromosome, Chromosome[])
                 *
                 * @param evaluator the fitness evaluator
                 * @param gtf the genotype factory
                 * @throws NullPointerException if one of the arguments is {@code null}.
                 */
                public Builder(
                        final Evaluator<G, C> evaluator,
                        final Factory<Genotype<G>> gtf
                ) {
                        _genotypeFactory = requireNonNull(gtf);
                        _evaluator = requireNonNull(evaluator);
                }

                /**
                 * Applies the given {@code setup} recipe to {@code this} engine builder.
                 *
                 * @since 6.0
                 *
                 * @param setup the setup recipe applying to {@code this} builder
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if the {@code setup} is {@code null}.
                 */
                public Builder<G, C> setup(final Setup<G, C> setup) {
                        setup.apply(this);
                        return this;
                }

                /**
                 * Set the evolution parameters used by the engine.
                 *
                 * @since 5.2
                 *
                 * @param params the evolution parameter
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if the {@code params} is {@code null}.
                 */
                public Builder<G, C> evolutionParams(final EvolutionParams<G, C> params) {
                        _evolutionParams.evolutionParams(params);
                        return this;
                }

                /**
                 * The selector used for selecting the offspring population. <i>Default
                 * values is set to {@code TournamentSelector<>(3)}.</i>
                 *
                 * @param selector used for selecting the offspring population
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if one of the {@code selector} is
                 *         {@code null}.
                 */
                public Builder<G, C> offspringSelector(final Selector<G, C> selector) {
                        _evolutionParams.offspringSelector(selector);
                        return this;
                }

                /**
                 * The selector used for selecting the survivor population. <i>Default
                 * values is set to {@code TournamentSelector<>(3)}.</i>
                 *
                 * @param selector used for selecting survivor population
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if one of the {@code selector} is
                 *         {@code null}.
                 */
                public Builder<G, C> survivorsSelector(final Selector<G, C> selector) {
                        _evolutionParams.survivorsSelector(selector);
                        return this;
                }

                /**
                 * The selector used for selecting the survivors and offspring
                 * population. <i>Default values is set to
                 * {@code TournamentSelector<>(3)}.</i>
                 *
                 * @param selector used for selecting survivors and offspring population
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if one of the {@code selector} is
                 *         {@code null}.
                 */
                public Builder<G, C> selector(final Selector<G, C> selector) {
                        _evolutionParams.selector(selector);
                        return this;
                }

                /**
                 * The alterers used for alter the offspring population. <i>Default
                 * values is set to {@code new SinglePointCrossover<>(0.2)} followed by
                 * {@code new Mutator<>(0.15)}.</i>
                 *
                 * @param first the first alterer used for alter the offspring
                 *        population
                 * @param rest the rest of the alterers used for alter the offspring
                 *        population
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if one of the alterers is {@code null}.
                 */
                @SafeVarargs
                public final Builder<G, C> alterers(
                        final Alterer<G, C> first,
                        final Alterer<G, C>... rest
                ) {
                        _evolutionParams.alterers(first, rest);
                        return this;
                }

                /**
                 * The phenotype constraint is used for detecting invalid individuals
                 * and repairing them.
                 *
                 * <p><i>Default implementation uses {@code Phenotype::isValid} for
                 * validating the phenotype.</i> Calling this method with {@code null}
                 * resets the builder to the default constraint.</p>
                 *
                 * @since 5.0
                 *
                 * @param constraint phenotype constraint which can override the default
                 *        implementation the {@link Phenotype#isValid()} method and repairs
                 *        invalid phenotypes when needed, or {@code null} for the default
                 *        constraint.
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> constraint(final Constraint<G, C> constraint) {
                        _constraint = constraint;
                        return this;
                }

                /**
                 * The optimization strategy used by the engine. <i>Default values is
                 * set to {@code Optimize.MAXIMUM}.</i>
                 *
                 * @param optimize the optimization strategy used by the engine
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if one of the {@code optimize} is
                 *         {@code null}.
                 */
                public Builder<G, C> optimize(final Optimize optimize) {
                        _optimize = requireNonNull(optimize);
                        return this;
                }

                /**
                 * Set to a fitness-maximizing strategy.
                 *
                 * @since 3.4
                 *
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> maximizing() {
                        return optimize(Optimize.MAXIMUM);
                }

                /**
                 * Set to a fitness minimizing strategy.
                 *
                 * @since 3.4
                 *
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> minimizing() {
                        return optimize(Optimize.MINIMUM);
                }

                /**
                 * The offspring fraction. <i>Default values is set to {@code 0.6}.</i>
                 * This method call is equivalent to
                 * {@code survivorsFraction(1 - offspringFraction)} and will override
                 * any previously set survivors-fraction.
                 *
                 * @see #survivorsFraction(double)
                 *
                 * @param fraction the offspring fraction
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if the fraction is not
                 *         within the range [0, 1].
                 */
                public Builder<G, C> offspringFraction(final double fraction) {
                        _evolutionParams.offspringFraction(fraction);
                        return this;
                }

                /**
                 * The survivor fraction. <i>Default values is set to {@code 0.4}.</i>
                 * This method call is equivalent to
                 * {@code offspringFraction(1 - survivorsFraction)} and will override
                 * any previously set offspring-fraction.
                 *
                 * @since 3.8
                 *
                 * @see #offspringFraction(double)
                 *
                 * @param fraction the survivor fraction
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if the fraction is not
                 *         within the range [0, 1].
                 */
                public Builder<G, C> survivorsFraction(final double fraction) {
                        return offspringFraction(1 - fraction);
                }

                /**
                 * The number of offspring individuals.
                 *
                 * @since 3.8
                 *
                 * @apiNote
                 * The offspring size is stored as a fraction of the current population
                 * size. Changing the population size afterwards keeps this fraction, not
                 * the absolute offspring size.
                 *
                 * @param size the number of offspring individuals.
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if the size is not
                 *         within the range [0, population-size].
                 */
                public Builder<G, C> offspringSize(final int size) {
                        if (size < 0) {
                                throw new IllegalArgumentException(format(
                                        "Offspring size must be greater or equal zero, but was %s.",
                                        size
                                ));
                        }

                        return offspringFraction(size/(double)_evolutionParams.populationSize());
                }

                /**
                 * The number of survivors.
                 *
                 * @since 3.8
                 *
                 * @apiNote
                 * The survivor size is stored as a fraction of the current population
                 * size. Changing the population size afterwards keeps this fraction, not
                 * the absolute survivor size.
                 *
                 * @param size the number of survivors.
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if the size is not
                 *         within the range [0, population-size].
                 */
                public Builder<G, C> survivorsSize(final int size) {
                        if (size < 0) {
                                throw new IllegalArgumentException(format(
                                        "Survivors must be greater or equal zero, but was %s.",
                                        size
                                ));
                        }

                        return survivorsFraction(size/(double)_evolutionParams.populationSize());
                }

                /**
                 * The number of individuals which form the population. <i>Default
                 * values is set to {@code 50}.</i>
                 *
                 * @param size the number of individuals of a population
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if {@code size < 1}
                 */
                public Builder<G, C> populationSize(final int size) {
                        _evolutionParams.populationSize(size);
                        return this;
                }

                /**
                 * The maximal allowed age of a phenotype. <i>Default value is set to
                 * {@code 70}.</i>
                 *
                 * @param age the maximal phenotype age
                 * @return {@code this} builder, for command chaining
                 * @throws java.lang.IllegalArgumentException if {@code age < 1}
                 */
                public Builder<G, C> maximalPhenotypeAge(final long age) {
                        _evolutionParams.maximalPhenotypeAge(age);
                        return this;
                }

                /**
                 * The executor used by the engine.
                 *
                 * @apiNote
                 * If no dedicated {@link Evaluator} is defined, this is also the
                 * executor, used for evaluating the fitness functions.
                 *
                 * @param executor the executor used by the engine
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> executor(final Executor executor) {
                        _executor = requireNonNull(executor);
                        return this;
                }

                /**
                 * This executor is used for evaluating the fitness functions.
                 *
                 * @apiNote
                 * If a dedicated {@link Evaluator} is defined, this executor is not
                 * used.
                 *
                 * @since 8.0
                 *
                 * @param executor the executor used for evaluating the fitness functions
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> fitnessExecutor(final BatchExecutor executor) {
                        _fitnessExecutor = requireNonNull(executor);
                        return this;
                }

                /**
                 * The clock used for calculating the execution durations.
                 *
                 * @param clock the clock used for calculating the execution durations
                 * @return {@code this} builder, for command chaining
                 */
                public Builder<G, C> clock(final InstantSource clock) {
                        _clock = requireNonNull(clock);
                        return this;
                }

                /**
                 * The evolution interceptor, which allows changing the evolution start
                 * and result.
                 *
                 * @since 6.0
                 * @see EvolutionResult#toUniquePopulation()
                 *
                 * @param interceptor the evolution interceptor
                 * @return {@code this} builder, for command chaining
                 * @throws NullPointerException if the given {@code interceptor} is
                 *         {@code null}
                 */
                public Builder<G, C>
                interceptor(final EvolutionInterceptor<G, C> interceptor) {
                        _interceptor = requireNonNull(interceptor);
                        return this;
                }

                /**
                 * Builds a new {@code Engine} instance from the set properties.
                 *
                 * @return a new {@code Engine} instance from the set properties
                 */
                public Engine<G, C> build() {
                        return new Engine<>(
                                __evaluator(),
                                _genotypeFactory,
                                __constraint(),
                                _optimize,
                                _evolutionParams.build(),
                                _executor,
                                _clock,
                                _interceptor
                        );
                }

                private Evaluator<G, C> __evaluator() {
                        return _evaluator instanceof FitnessEvaluator<G, C> fe
                                ? new FitnessEvaluator<>(fe.function(), fitnessExecutor())
                                : _evaluator;
                }

                private Constraint<G, C> __constraint() {
                        return _constraint == null
                                ? RetryConstraint.of(_genotypeFactory)
                                : _constraint;
                }

                /* *********************************************************************
                 * Current properties
                 ***********************************************************************/

                /**
                 * Return the used {@link Alterer} of the GA.
                 *
                 * @return the used {@link Alterer} of the GA.
                 */
                public Alterer<G, C> alterer() {
                        return _evolutionParams.alterer();
                }

                /**
                 * Return the {@link InstantSource} the engine is using for measuring
                 * the execution time.
                 *
                 * @since 3.1
                 *
                 * @return the clock used for measuring the execution time
                 */
                public InstantSource clock() {
                        return _clock;
                }

                /**
                 * Return the {@link Executor} the engine is using for executing the
                 * evolution steps.
                 *
                 * @since 3.1
                 *
                 * @return the executor used for performing the evolution steps
                 */
                public Executor executor() {
                        return _executor;
                }

                /**
                 * Return the batch executor, used for evaluating the fitness functions.
                 *
                 * @since 8.0
                 *
                 * @return the batch executor, used for evaluating the fitness functions
                 */
                public BatchExecutor fitnessExecutor() {
                        return _fitnessExecutor != null
                                ? _fitnessExecutor
                                : BatchExecutor.of(executor());
                }

                /**
                 * Return the used genotype {@link Factory} of the GA. The genotype factory
                 * is used for creating the initial population and new, random individuals
                 * when needed (as replacement for invalid and/or died genotypes).
                 *
                 * @since 3.1
                 *
                 * @return the used genotype {@link Factory} of the GA.
                 */
                public Factory<Genotype<G>> genotypeFactory() {
                        return _genotypeFactory;
                }

                /**
                 * Return the constraint of the evolution problem.
                 *
                 * @since 5.0
                 *
                 * @return the constraint of the evolution problem
                 */
                public Constraint<G, C> constraint() {
                        return _constraint;
                }

                /**
                 * Return the currently set evolution parameters.
                 *
                 * @since 5.2
                 *
                 * @return the currently set evolution parameters
                 */
                public EvolutionParams<G, C> evolutionParams() {
                        return _evolutionParams.build();
                }

                /**
                 * Return the maximal allowed phenotype age.
                 *
                 * @since 3.1
                 *
                 * @return the maximal allowed phenotype age
                 */
                public long maximalPhenotypeAge() {
                        return _evolutionParams.maximalPhenotypeAge();
                }

                /**
                 * Return the offspring fraction.
                 *
                 * @return the offspring fraction.
                 */
                public double offspringFraction() {
                        return _evolutionParams.offspringFraction();
                }

                /**
                 * Return the used offspring {@link Selector} of the GA.
                 *
                 * @since 3.1
                 *
                 * @return the used offspring {@link Selector} of the GA.
                 */
                public Selector<G, C> offspringSelector() {
                        return _evolutionParams.offspringSelector();
                }

                /**
                 * Return the used survivor {@link Selector} of the GA.
                 *
                 * @since 3.1
                 *
                 * @return the used survivor {@link Selector} of the GA.
                 */
                public Selector<G, C> survivorsSelector() {
                        return _evolutionParams.survivorsSelector();
                }

                /**
                 * Return the optimization strategy.
                 *
                 * @since 3.1
                 *
                 * @return the optimization strategy
                 */
                public Optimize optimize() {
                        return _optimize;
                }

                /**
                 * Return the number of individuals of a population.
                 *
                 * @since 3.1
                 *
                 * @return the number of individuals of a population
                 */
                public int populationSize() {
                        return _evolutionParams.populationSize();
                }

                /**
                 * Return the evolution interceptor.
                 *
                 * @since 6.0
                 *
                 * @return the evolution interceptor
                 */
                public EvolutionInterceptor<G, C> interceptor() {
                        return _interceptor;
                }

                /**
                 * Create a new builder, with the current configuration.
                 *
                 * @apiNote
                 * For builders created from a fitness function, a configured fitness
                 * executor is not copied. Calling {@link #fitnessExecutor(BatchExecutor)}
                 * on the copied builder creates a new fitness evaluator with the given
                 * executor.
                 *
                 * @since 3.1
                 *
                 * @return a new builder, with the current configuration
                 */
                @Override
                public Builder<G, C> copy() {
                        return new Builder<>(_evaluator, _genotypeFactory)
                                .clock(_clock)
                                .executor(_executor)
                                .constraint(_constraint)
                                .optimize(_optimize)
                                .evolutionParams(_evolutionParams.build())
                                .interceptor(_interceptor);
                }

        }


        /* *************************************************************************
         * Engine setup
         **************************************************************************/


        /**
         * This interface represents a recipe for configuring (setup) a given
         * {@link Builder}. It is mainly used for grouping mutually dependent
         * engine configurations. The following code snippet shows a possible usage
         * example.
         * {@snippet lang="java":
         * final Engine<CharacterGene, Integer> engine = Engine.builder(problem)
         *     .setup(new WeaselProgram<>())
         *     .build();
         * }
         *
         * @see Builder#setup(Setup)
         *
         * @param <G> the gene type
         * @param <C> the fitness result type
         *
         * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
         * @version 6.0
         * @since 6.0
         */
        @FunctionalInterface
        public interface Setup<
                G extends Gene<?, G>,
                C extends Comparable<? super C>
        > {

                /**
                 * Applies {@code this} setup to the given engine {@code builder}.
                 *
                 * @param builder the engine builder to set up (configure)
                 */
                void apply(final Builder<G, C> builder);

        }
}