List scheduling combined with genetic algorithms has already been shown to be a powerful approach [6, 11 ]. We investigate the problems associated with using a list scheduler for a heterogeneous system. Furthermore, we present cases, from which most list schedulers fail to find the optimum. We propose and experimentally evaluate novel ideas avoiding it.