Evojav -

// 2. Main evolution loop public class Optimizer public static void main(String[] args) EvoJavaEngine<MySolution> engine = EvoJavaEngine .<MySolution>builder() .populationSize(200) .generations(100) .fitnessFunction(sol -> sol.getGenome() * Math.sin(sol.getGenome())) .crossoverOperator((a, b) -> (a + b) / 2) // blend crossover .mutationOperator(gene -> gene + (int)(Math.random() * 5 - 2)) .selectionStrategy(Selection.TOURNAMENT) .build();

// 1. Define the individual (a simple integer gene) public class MySolution implements Individual<Integer> private int value; public MySolution(int val) this.value = val; evojav

But what if your requirements are fuzzy? What if the optimal solution to your problem isn't something you can logically deduce, but something the computer has to discover ? engine = EvoJavaEngine .&lt

EvolutionResult<MySolution> result = engine.evolve(); private int value

System.out.println("Best solution found: " + result.bestIndividual()); System.out.println("Fitness: " + result.bestFitness());