/*
 * 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.util.Objects.requireNonNull;
import static java.util.stream.Collectors.toMap;
import static io.jenetics.engine.EvolutionInterceptor.ofAfter;
import static io.jenetics.internal.util.SerialIO.readInt;
import static io.jenetics.internal.util.SerialIO.readLong;
import static io.jenetics.internal.util.SerialIO.writeInt;
import static io.jenetics.internal.util.SerialIO.writeLong;

import java.io.IOException;
import java.io.InvalidObjectException;
import java.io.ObjectInput;
import java.io.ObjectInputStream;
import java.io.ObjectOutput;
import java.io.Serial;
import java.io.Serializable;
import java.util.Map;
import java.util.Objects;
import java.util.function.Function;
import java.util.stream.Collector;
import java.util.stream.Stream;

import io.jenetics.Gene;
import io.jenetics.Genotype;
import io.jenetics.Optimize;
import io.jenetics.Phenotype;
import io.jenetics.internal.util.Lazy;
import io.jenetics.stat.MinMax;
import io.jenetics.util.Factory;
import io.jenetics.util.ISeq;
import io.jenetics.util.Seq;

/**
 * Represents a state of the GA after an evolution step. It also represents the
 * final state of an evolution process and can be created with an appropriate
 * collector:
 * {@snippet lang="java":
 * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
 * final EvolutionResult<EnumGene<Point>, Double> result = Engine.builder(tsm)
 *     .optimize(Optimize.MINIMUM)
 *     .build()
 *     .stream()
 *     .limit(100)
 *     .collect(EvolutionResult.toBestEvolutionResult());
 * }
 *
 * @implSpec
 * This class implements the {@link Comparable} interface, which compares two
 * {@link EvolutionResult} objects according its <em>optimal</em> fitness value.
 * This means that the better evolution result is always <em>greater</em>, no
 * matter if the fitness function is minimized or maximized.
 * {@snippet lang="java":
 * final EvolutionResult<DoubleGene, Double> result1 = null; // @replace substring='null' replacement="..."
 * final EvolutionResult<DoubleGene, Double> result2 = null; // @replace substring='null' replacement="..."
 *
 * if (result1.compareTo(result2) > 0) {
 *      // Holds for maximizing evolution results.
 *     assert result1.bestFitness() > result2.bestFitness();
 *
 *     // Holds for minimizing evolution results.
  *    assert result1.bestFitness() < result2.bestFitness();
 * }
 * }
 *
 * @see EvolutionStart
 * @see Engine
 *
 * @param <G> the gene type
 * @param <C> the fitness type
 *
 * @implNote
 * This class is immutable and thread-safe.
 *
 * @author <a href="mailto:franz.wilhelmstoetter@gmail.com">Franz Wilhelmstötter</a>
 * @since 3.0
 * @version 6.0
 */
public final class EvolutionResult<
        G extends Gene<?, G>,
        C extends Comparable<? super C>
>
        implements Comparable<EvolutionResult<G, C>>, Serializable
{
        @Serial
        private static final long serialVersionUID = 2L;

        private final Optimize _optimize;
        private final ISeq<Phenotype<G, C>> _population;
        private final long _generation;
        private final long _totalGenerations;

        private final EvolutionDurations _durations;
        private final int _killCount;
        private final int _invalidCount;
        private final int _alterCount;

        private final boolean _dirty;

        private final Lazy<Phenotype<G, C>> _best;
        private final Lazy<Phenotype<G, C>> _worst;

        private EvolutionResult(
                final Optimize optimize,
                final ISeq<Phenotype<G, C>> population,
                final long generation,
                final long totalGenerations,
                final EvolutionDurations durations,
                final int killCount,
                final int invalidCount,
                final int alterCount,
                final boolean dirty
        ) {
                _optimize = requireNonNull(optimize);
                _population = requireNonNull(population);
                _generation = generation;
                _totalGenerations = totalGenerations;
                _durations = requireNonNull(durations);
                _killCount = killCount;
                _invalidCount = invalidCount;
                _alterCount = alterCount;
                _dirty = dirty;

                _best = Lazy.of(() -> _population.stream()
                        .max(_optimize.ascending())
                        .orElse(null)
                );

                _worst = Lazy.of(() -> _population.stream()
                        .min(_optimize.ascending())
                        .orElse(null)
                );
        }

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

        /**
         * Return the population after the evolution step.
         *
         * @return the population after the evolution step
         */
        public ISeq<Phenotype<G, C>> population() {
                return _population;
        }

        /**
         * Return the current list of genotypes of this evolution result.
         *
         * @since 5.2
         *
         * @return the list of genotypes of this evolution result.
         */
        public ISeq<Genotype<G>> genotypes() {
                return _population.map(Phenotype::genotype);
        }

        /**
         * The current generation.
         *
         * @return the current generation
         */
        public long generation() {
                return _generation;
        }

        /**
         * Return the generation count evaluated so far.
         *
         * @return the total number of generations evaluated so far
         */
        public long totalGenerations() {
                return _totalGenerations;
        }

        /**
         * Return the timing (meta) information of the evolution step.
         *
         * @return the timing (meta) information of the evolution step
         */
        public EvolutionDurations durations() {
                return _durations;
        }

        /**
         * Return the number of killed individuals.
         *
         * @return the number of killed individuals
         */
        public int killCount() {
                return _killCount;
        }

        /**
         * Return the number of invalid individuals.
         *
         * @return the number of invalid individuals
         */
        public int invalidCount() {
                return _invalidCount;
        }

        /**
         * The number of altered individuals.
         *
         * @return the number of altered individuals
         */
        public int alterCount() {
                return _alterCount;
        }

        /**
         * Return the best {@code Phenotype} of the result population.
         *
         * @return the best {@code Phenotype} of the result population
         */
        public Phenotype<G, C> bestPhenotype() {
                return _best.get();
        }

        /**
         * Return the worst {@code Phenotype} of the result population.
         *
         * @return the worst {@code Phenotype} of the result population
         */
        public Phenotype<G, C> worstPhenotype() {
                return _worst.get();
        }

        /**
         * Return the best population fitness.
         *
         * @return The best population fitness.
         */
        public C bestFitness() {
                return _best.get() != null
                        ? _best.get().fitness()
                        : null;
        }

        /**
         * Return the worst population fitness.
         *
         * @return The worst population fitness.
         */
        public C worstFitness() {
                return _worst.get() != null ? _worst.get().fitness() : null;
        }

        /**
         * Return the next evolution start object with the current population and
         * the incremented generation.
         *
         * @since 4.1
         *
         * @return the next evolution start object
         */
        public EvolutionStart<G, C> next() {
                return new EvolutionStart<>(_population, _totalGenerations + 1, _dirty);
        }

        /**
         * Return the current evolution result object as an {@code EvolutionStart}
         * object with the current population and current total generation.
         *
         * @since 4.1
         *
         * @return the current result as evolution start
         */
        public EvolutionStart<G, C> toEvolutionStart() {
                return new EvolutionStart<>(_population, _totalGenerations, _dirty);
        }

        /**
         * Compare {@code this} evolution result with another one, according the
         * population's best individual.
         *
         * @param other the other evolution result to compare
         * @return  a negative integer, zero, or a positive integer as this result
         *          is less than, equal to, or greater than the specified result.
         */
        @Override
        public int compareTo(final EvolutionResult<G, C> other) {
                return _optimize.compare(_best.get(), other._best.get());
        }

        private EvolutionResult<G, C> withTotalGenerations(final long total) {
                return EvolutionResult.of(
                        _optimize,
                        _population,
                        _generation,
                        total,
                        _durations,
                        _killCount,
                        _invalidCount,
                        _alterCount
                );
        }

        EvolutionResult<G, C> withPopulation(final ISeq<Phenotype<G, C>> population) {
                return EvolutionResult.of(
                        optimize(),
                        population,
                        generation(),
                        totalGenerations(),
                        durations(),
                        killCount(),
                        invalidCount(),
                        alterCount()
                );
        }

        EvolutionResult<G, C> withDurations(final EvolutionDurations durations) {
                return EvolutionResult.of(
                        optimize(),
                        population(),
                        generation(),
                        totalGenerations(),
                        durations,
                        killCount(),
                        invalidCount(),
                        alterCount()
                );
        }

        EvolutionResult<G, C> clean() {
                return new EvolutionResult<>(
                        optimize(),
                        population(),
                        generation(),
                        totalGenerations(),
                        durations(),
                        killCount(),
                        invalidCount(),
                        alterCount(),
                        false
                );
        }

        @Override
        public int hashCode() {
                return Objects.hash(
                        _optimize,
                        _population,
                        _generation,
                        _totalGenerations,
                        _durations,
                        _killCount,
                        _invalidCount,
                        _alterCount
                );
        }

        @Override
        public boolean equals(final Object obj) {
                return obj instanceof EvolutionResult<?, ?> other &&
                        Objects.equals(_optimize, other._optimize) &&
                        Objects.equals(_population, other._population) &&
                        Objects.equals(_generation, other._generation) &&
                        Objects.equals(_totalGenerations, other._totalGenerations) &&
                        Objects.equals(_durations, other._durations) &&
                        Objects.equals(_killCount, other._killCount) &&
                        Objects.equals(_invalidCount, other._invalidCount) &&
                        Objects.equals(_alterCount, other._alterCount);
        }


        /* *************************************************************************
         *  Some static collector/factory methods.
         * ************************************************************************/


        /**
         * Return a collector which collects the best result of an evolution stream.
         * {@snippet lang="java":
         * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
         * final EvolutionResult<EnumGene<Point>, Double> result = Engine.builder(tsm)
         *     .optimize(Optimize.MINIMUM).build()
         *     .stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestEvolutionResult());
         * }
         *
         * If the collected {@link EvolutionStream} is empty, the collector returns
         * <b>{@code null}</b>.
         *
         * @param <G> the gene type
         * @param <C> the fitness type
         * @return a collector which collects the best result of an evolution stream
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        Collector<EvolutionResult<G, C>, ?, EvolutionResult<G, C>>
        toBestEvolutionResult() {
                return Collector.of(
                        MinMax::of,
                        MinMax::accept,
                        MinMax::combine,
                        (MinMax<EvolutionResult<G, C>> mm) -> mm.max() != null
                                ? mm.max().withTotalGenerations(mm.count())
                                : null
                );
        }

        /**
         * Return a collector which collects the best phenotype of an evolution
         * stream.
         * {@snippet lang="java":
         * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
         * final Phenotype<EnumGene<Point>, Double> result = Engine.builder(tsm)
         *     .optimize(Optimize.MINIMUM).build()
         *     .stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestPhenotype());
         * }
         *
         * If the collected {@link EvolutionStream} is empty, the collector returns
         * <b>{@code null}</b>.
         *
         * @param <G> the gene type
         * @param <C> the fitness type
         * @return a collector which collects the best phenotype of an evolution
         *         stream
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        Collector<EvolutionResult<G, C>, ?, Phenotype<G, C>>
        toBestPhenotype() {
                return Collector.of(
                        MinMax::of,
                        MinMax::accept,
                        MinMax::combine,
                        (MinMax<EvolutionResult<G, C>> mm) -> mm.max() != null
                                ? mm.max().bestPhenotype()
                                : null
                );
        }

        /**
         * Return a collector which collects the best genotype of an evolution
         * stream.
         * {@snippet lang="java":
         * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
         * final Genotype<EnumGene<Point>> result = Engine.builder(tsm)
         *     .optimize(Optimize.MINIMUM).build()
         *     .stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestGenotype());
         * }
         *
         * If the collected {@link EvolutionStream} is empty, the collector returns
         * <b>{@code null}</b>.
         *
         * @param <G> the gene type
         * @param <C> the fitness type
         * @return a collector which collects the best genotype of an evolution
         *         stream
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        Collector<EvolutionResult<G, C>, ?, Genotype<G>>
        toBestGenotype() {
                return Collector.of(
                        MinMax::of,
                        MinMax::accept,
                        MinMax::combine,
                        (MinMax<EvolutionResult<G, C>> mm) -> mm.max() != null
                                ? mm.max().bestPhenotype() != null
                                        ? mm.max().bestPhenotype().genotype()
                                        : null
                                : null
                );
        }

        /**
         * Return a collector which collects the best <em>result</em> (in the native
         * problem space).
         * {@snippet lang="java":
         * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
         * final ISeq<Point> route = Engine.builder(tsm)
         *     .optimize(Optimize.MINIMUM).build()
         *     .stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestResult(tsm.codec().decoder()));
         * }
         *
         * If the collected {@link EvolutionStream} is empty, the collector returns
         * <b>{@code null}</b>.
         *
         * @since 3.6
         *
         * @param decoder the decoder which converts the {@code Genotype} into the
         *        result of the problem space.
         * @param <T> the <em>native</em> problem result type
         * @param <G> the gene type
         * @param <C> the fitness result type
         * @return a collector which collects the best result of an evolution stream
         * @throws NullPointerException if the given {@code decoder} is {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>, T>
        Collector<EvolutionResult<G, C>, ?, T>
        toBestResult(final Function<Genotype<G>, T> decoder) {
                requireNonNull(decoder);

                return Collector.of(
                        MinMax::of,
                        MinMax::accept,
                        MinMax::combine,
                        (MinMax<EvolutionResult<G, C>> mm) -> mm.max() != null
                                ? mm.max().bestPhenotype() != null
                                        ? decoder.apply(mm.max().bestPhenotype().genotype())
                                        : null
                                : null
                );
        }

        /**
         * Return a collector which collects the best <em>result</em> (in the native
         * problem space).
         * {@snippet lang="java":
         * final Problem<ISeq<Point>, EnumGene<Point>, Double> tsm = null; // @replace substring='null' replacement="..."
         * final ISeq<Point> route = Engine.builder(tsm)
         *     .optimize(Optimize.MINIMUM).build()
         *     .stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestResult(tsm.codec()));
         * }
         *
         * If the collected {@link EvolutionStream} is empty, the collector returns
         * <b>{@code null}</b>.
         *
         * @since 3.6
         *
         * @param codec the problem decoder
         * @param <T> the <em>native</em> problem result type
         * @param <G> the gene type
         * @param <C> the fitness result type
         * @return a collector which collects the best result of an evolution stream
         * @throws NullPointerException if the given {@code codec} is {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>, T>
        Collector<EvolutionResult<G, C>, ?, T>
        toBestResult(final Codec<T, G> codec) {
                return toBestResult(codec.decoder());
        }

        /**
         * Return a mapping function, which removes duplicate individuals from the
         * population and replaces it with newly created one by the given genotype
         * {@code factory}.
         * {@snippet lang="java":
         * final Problem<Double, DoubleGene, Integer> problem = null; // @replace substring='null' replacement="..."
         * final Engine<DoubleGene, Integer> engine = Engine.builder(problem)
         *     .interceptor(toUniquePopulation(problem.codec().encoding(), 100))
         *     .build();
         * final Genotype<DoubleGene> best = engine.stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestGenotype());
         * }
         *
         * @since 6.0
         * @see Engine.Builder#interceptor(EvolutionInterceptor)
         *
         * @param factory the genotype factory which creates new individuals
         * @param maxRetries the maximal number of genotype creations tries
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return  a mapping function, which removes duplicate individuals from the
         *          population
         * @throws NullPointerException if the given genotype {@code factory} is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionInterceptor<G, C>
        toUniquePopulation(final Factory<Genotype<G>> factory, final int maxRetries) {
                requireNonNull(factory);
                return ofAfter(result -> uniquePopulation(factory, maxRetries, result));
        }

        private static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionResult<G, C> uniquePopulation(
                final Factory<Genotype<G>> factory,
                final int maxRetries,
                final EvolutionResult<G, C> result
        ) {
                final Seq<Phenotype<G, C>> population = result.population();
                final Map<Genotype<G>, Phenotype<G, C>> elements =
                        population.stream()
                                .collect(toMap(
                                        Phenotype::genotype,
                                        Function.identity(),
                                        (a, _) -> a));

                EvolutionResult<G, C> uniques = result;
                if (elements.size() < population.size()) {
                        int retries = 0;
                        while (elements.size() < population.size() && retries < maxRetries) {
                                final Genotype<G> gt = factory.newInstance();
                                final Phenotype<G, C> pt = elements
                                        .put(gt, Phenotype.of(gt, result.generation()));
                                if (pt != null) {
                                        ++retries;
                                }
                        }
                        uniques = result.withPopulation(
                                Stream.concat(elements.values().stream(), population.stream())
                                        .limit(population.size())
                                        .collect(ISeq.toISeq())
                        );
                }

                return uniques;
        }


        /* *************************************************************************
         * Some collector and mapping functions.
         * ************************************************************************/


        /**
         * Return a mapping function, which removes duplicate individuals from the
         * population and replaces it with newly created one by the given genotype
         * {@code factory}.
         * {@snippet lang="java":
         * final Problem<Double, DoubleGene, Integer> problem = null; // @replace substring='null' replacement="..."
         * final Engine<DoubleGene, Integer> engine = Engine.builder(problem)
         *     .interceptor(toUniquePopulation(problem.codec().encoding()))
         *     .build();
         * final Genotype<DoubleGene> best = engine.stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestGenotype());
         * }
         *
         * @since 6.0
         * @see Engine.Builder#interceptor(EvolutionInterceptor)
         *
         * @param factory the genotype factory which creates new individuals
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return  a mapping function, which removes duplicate individuals from the
         *          population
         * @throws NullPointerException if the given genotype {@code factory} is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionInterceptor<G, C>
        toUniquePopulation(final Factory<Genotype<G>> factory) {
                return toUniquePopulation(factory, 100);
        }

        /**
         * Return a mapping function, which removes duplicate individuals from the
         * population and replaces it with newly created one by the existing
         * genotype factory.
         * {@snippet lang="java":
         * final Problem<Double, DoubleGene, Integer> problem = null; // @replace substring='null' replacement="..."
         * final Engine<DoubleGene, Integer> engine = Engine.builder(problem)
         *     .interceptor(toUniquePopulation(10))
         *     .build();
         * final Genotype<DoubleGene> best = engine.stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestGenotype(5));
         * }
         *
         * @since 6.0
         * @see Engine.Builder#interceptor(EvolutionInterceptor)
         *
         * @param maxRetries the maximal number of genotype creations tries
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return  a mapping function, which removes duplicate individuals from the
         *          population
         * @throws NullPointerException if the given genotype {@code factory} is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionInterceptor<G, C> toUniquePopulation(final int maxRetries) {
                return ofAfter(result -> uniquePopulation(
                        result.population().get(0).genotype(),
                        maxRetries,
                        result
                ));
        }

        /**
         * Return a mapping function, which removes duplicate individuals from the
         * population and replaces it with newly created one by the existing
         * genotype factory.
         * {@snippet lang="java":
         * final Problem<Double, DoubleGene, Integer> problem = null; // @replace substring='null' replacement="..."
         * final Engine<DoubleGene, Integer> engine = Engine.builder(problem)
         *     .interceptor(EvolutionResult.toUniquePopulation())
         *     .build();
         * final Genotype<DoubleGene> best = engine.stream()
         *     .limit(100)
         *     .collect(EvolutionResult.toBestGenotype());
         * }
         *
         * @since 6.0
         * @see Engine.Builder#interceptor(EvolutionInterceptor)
         *
         * @param <G> the gene type
         * @param <C> the fitness function result type
         * @return  a mapping function, which removes duplicate individuals from the
         *          population
         * @throws NullPointerException if the given genotype {@code factory} is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionInterceptor<G, C> toUniquePopulation() {
                return ofAfter(result -> uniquePopulation(
                        result.population().get(0).genotype(),
                        100,
                        result
                ));
        }

        /**
         * Return a new {@code EvolutionResult} object with the given values.
         *
         * @param optimize the optimization strategy used
         * @param population the population after the evolution step
         * @param generation the current generation
         * @param totalGenerations the overall number of generations
         * @param durations the timing (meta) information
         * @param killCount the number of individuals which has been killed
         * @param invalidCount the number of individuals which has been removed as
         *        invalid
         * @param alterCount the number of individuals which has been altered
         * @param <G> the gene type
         * @param <C> the fitness type
         * @return an new evolution result object
         * @throws java.lang.NullPointerException if one of the parameters is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionResult<G, C> of(
                final Optimize optimize,
                final ISeq<Phenotype<G, C>> population,
                final long generation,
                final long totalGenerations,
                final EvolutionDurations durations,
                final int killCount,
                final int invalidCount,
                final int alterCount
        ) {
                return new EvolutionResult<>(
                        optimize,
                        population,
                        generation,
                        totalGenerations,
                        durations,
                        killCount,
                        invalidCount,
                        alterCount,
                        true
                );
        }

        /**
         * Return a new {@code EvolutionResult} object with the given values.
         *
         * @param optimize the optimization strategy used
         * @param population the population after the evolution step
         * @param generation the current generation
         * @param durations the timing (meta) information
         * @param killCount the number of individuals which has been killed
         * @param invalidCount the number of individuals which has been removed as
         *        invalid
         * @param alterCount the number of individuals which has been altered
         * @param <G> the gene type
         * @param <C> the fitness type
         * @return an new evolution result object
         * @throws java.lang.NullPointerException if one of the parameters is
         *         {@code null}
         */
        public static <G extends Gene<?, G>, C extends Comparable<? super C>>
        EvolutionResult<G, C> of(
                final Optimize optimize,
                final ISeq<Phenotype<G, C>> population,
                final long generation,
                final EvolutionDurations durations,
                final int killCount,
                final int invalidCount,
                final int alterCount
        ) {
                return new EvolutionResult<>(
                        optimize,
                        population,
                        generation,
                        generation,
                        durations,
                        killCount,
                        invalidCount,
                        alterCount,
                        true
                );
        }


        /* *************************************************************************
         *  Java object serialization
         * ************************************************************************/

        @Serial
        private Object writeReplace() {
                return new SerialProxy(SerialProxy.EVOLUTION_RESULT, this);
        }

        @Serial
        private void readObject(final ObjectInputStream stream)
                throws InvalidObjectException
        {
                throw new InvalidObjectException("Serialization proxy required.");
        }

        void write(final ObjectOutput out) throws IOException {
                out.writeObject(_optimize);
                out.writeObject(_population);
                writeLong(_generation, out);
                writeLong(_totalGenerations, out);
                out.writeObject(_durations);
                writeInt(_killCount, out);
                writeInt(_invalidCount, out);
                writeInt(_alterCount, out);
        }

        @SuppressWarnings({"unchecked", "rawtypes"})
        static Object read(final ObjectInput in)
                throws IOException, ClassNotFoundException
        {
                return new EvolutionResult<>(
                        (Optimize)in.readObject(),
                        (ISeq)in.readObject(),
                        readLong(in),
                        readLong(in),
                        (EvolutionDurations)in.readObject(),
                        readInt(in),
                        readInt(in),
                        readInt(in),
                        true
                );
        }

}