An investigation of cooperative dispatching for minimising mean flowtime in a finite-buffer-capacity dynamic flowshop

Scheduling in a dynamic flowshop that receives jobs at random and unforeseen points in time has traditionally been done by using dispatching rules. This study compares the performances of leading dispatching rules with a cooperative dispatching approach, for the objective of minimising mean flowtime in a flowshop, in which the buffers that hold in-process jobs between machines have finite capacities. Cooperative dispatching employs a consultative and consensus-seeking methodology for deciding which job to dispatch next on a machine. Computational experiments using randomly generated test problems for three different utilisation (congestion) levels are carried out for 5- and 10-machine flowshops, under a wide range of buffer capacities. The results highlight the sensitivity of some of the popular dispatching rules to buffer size. In contrast, cooperative dispatching emerges as a robust method that performs consistently well across the range of buffer sizes and machine utilisations tested. The reductions in mean flowtime obtained by cooperative dispatching, in comparison to the other dispatching rules, are particularly large in flowshops that operate with very tight buffer capacities and elevated levels of congestion