  We demonstrate how a genetic algorithm solves the problem of minimizing the
resources used for network coding, subject to a throughput constraint, in a
multicast scenario. A genetic algorithm avoids the computational complexity
that makes the problem NP-hard and, for our experiments, greatly improves on
sub-optimal solutions of established methods. We compare two different genotype
encodings, which tradeoff search space size with fitness landscape, as well as
the associated genetic operators. Our finding favors a smaller encoding despite
its fewer intermediate solutions and demonstrates the impact of the modularity
enforced by genetic operators on the performance of the algorithm.
