// Guessing of the array content

    alias Chromosome!(ScalarGene!bool) chromoType;   // define chromosome type

    //init target array
    enum size = 20;
    bool[] target;

    foreach(i; 0..size)
    {
        target ~= dice(0.5, 0.5) == 1;
    }

    //create GA configuration
    auto conf = new Configuration!chromoType(new chromoType(new ScalarGene!bool(), size)); //config with sample chromosome to init population with
    conf.populationSize = 10;   //size of the population

    //set fitness function
    conf.fitnessFunction = simpleFitness!chromoType(delegate (ch)
    {
        //add to tmp if chromosome and target are same so max fitness = 20
        uint tmp;
        foreach(i; 0..size)
        {
            if(target[i] == ch[i]) ++tmp;
        }

        return cast(double)tmp;
    });

    //set terminate function
    conf.terminateFunction = compositeTerminate( //GA is terminated if one of conditions is met
        maxGenerationsTerminate!(100),  //limit to max 100 generations
        fitnessTerminate!size); //target fitness is size of genomes

    //add GA operations
    conf.eliteSelectionOperator = eliteSelection!chromoType; // best chromosome allways survives
    conf.parentSelectionOperator = weightedRouletteSelection!chromoType(); //select parent chromosomes to crossover and mutate
    conf.crossoverOperator = singlePointCrossover!chromoType(); //type of crossover operator

    //execute GA
    auto ga = new GA!chromoType(conf);
    ga.run(); //does return after one of terminate condition is met

    writefln("Input: [%s]", target.map!(to!string).joiner(", "));
    writefln("Best: [%s]", ga.population.best);