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Suppose that the objective function takes binary input and returns the sum of the values as

def f(x: List[Int]): Double = x.sum * 1.0

and it is clear that any List with values (0, 0, ..., 0) minimized f. The scala implementation of Compact Genetic Algorithms can be used to minimize this function using

val result = GA.cga(f, 10, 0.001)

where f is the objective function defined above, 10 is the bit length, 0.001 is the amount of mutation in each single iteration. The result is a List[Int] object with size 10:

List(0, 0, 0, 0, 0, 0, 0, 0, 0, 0)

The user is asked to provide these three information as input.