pGA

pGA(
    // Set a population configuration
    population = population(size = 200) { booleans(size = 100) },
    // Set a fitness function
    fitnessFunction = { value -> value.count { it } },
) {
    random = Random(seed = 42) // set pseudo random number generator
    elitism = 10 // set elitism

    before {
        println("GA STARTED, Init population: $population")
    }

    // create evolution strategy
    evolve {
        selTournament(size = 3, parallelismLimit = NO_PARALLELISM) // select
        cxOnePoint(chance = 0.8) // crossover
        mutFlipBit(chance = 0.2, flipBitChance = 0.01) // mutate
        evaluation() // evaluate population
        stopBy(maxIteration = 50) { bestFitness == 100 } // finish GA by conditions
    }

    after {
        println("GA FINISHED, Result = $best")
    }
}.startBlocking()