Search-enhanced job dispatching in a dynamic permutation flowshop

A dynamic flowshop that continuously receives jobs at random points in time is considered, with the objective of scheduling the jobs in an order that minimizes the mean flowtime. A tabu search is proposed for deciding which job to dispatch next to the flowshop, and the approach is then compared by means of a computational analysis with a number of other competing dispatching rules. The results demonstrate that the search-enhanced dispatching method achieves reductions of between 13% and 17% in the mean flowtimes in comparison to the other dispatching rules. However, the proposed method is not as competitive in comparison to a more complex cooperative dispatching approach when shop congestion levels are medium to low.