  Many academic disciplines - including information systems, computer science,
and operations management - face scheduling problems as important decision
making tasks. Since many scheduling problems are NP-hard in the strong sense,
there is a need for developing solution heuristics. For scheduling problems
with setup times on unrelated parallel machines, there is limited research on
solution methods and to the best of our knowledge, parallel computer
architectures have not yet been taken advantage of. We address this gap by
proposing and implementing a new solution heuristic and by testing different
parallelization strategies. In our computational experiments, we show that our
heuristic calculates near-optimal solutions even for large instances and that
computing time can be reduced substantially by our parallelization approach.
