  We study heuristic algorithms for job shop scheduling problems.
  We compare classical approaches, such as the shifting bottleneck heuristic
with novel strategies using decision diagrams. Balas' local refinement is used
to improve feasible solutions. Heuristic approaches are combined with Mixed
Integer Programming and Constraint Programming approaches. We discuss our
results via computational experiments.
