Online scheduling of 2-re-entrant flexible manufacturing systems

Online scheduling of operations is essential to optimize productivity of flexible manufacturing systems (FMSs) where manufacturing requests arrive on the fly. An FMS processes products according to a particular flow through processing stations. This work focusses on online scheduling of re-entrant FMSs with flows using processing stations where products pass twice and with limited buffering between processing stations. This kind of FMS is modelled as a re-entrant flow shop with due dates and sequence-dependent set-up times. Such flow shops can benefit from minimization of the time penalties incurred from set-up times. On top of an existing greedy scheduling heuristic we apply a meta-heuristic that simultaneously explores several alternatives considering trade-offs between the used metrics by the scheduling heuristic. We identify invariants to efficiently remove many infeasible scheduling options so that the running time of online implementations is improved. The resulting algorithm is much faster than the state of the art and produces schedules with on average 4.6% shorter makespan