Many application domains resolve to the use of synthetic test data motivated by privacy concerns and safety reasons, but also, on the positive side, due to cost and quality considerations. Genetic Algorithms have long been studied for graph optimisation, however, to the best of our knowledge, not for scheme plan generation. We present a new approach that automatically constructs scheme plans from a set of tiles. This transforms the scheme plan generation problem into a combinatorial optimisation process. The manual design of scheme plans is laborious, costly, and in itself an error-prone process. Thus, there is a demand in the rail industry for synthetic scheme plans. All constructions are given. The runtimes achieved by our tool are presented.