The size of realistic public transport networks is often a problem in algorithmic approaches for line planning, timetabling and vehicle scheduling. This paper describes a possibility to use human experience to reduce the instance sizes but still find good solutions for the original network. To this end, we introduce novel network objects called system routes. In computational experiments, this does not only decrease the runtime needed to find solutions but increases the solution quality as well.