# Linking Scheduling Criteria to Shop Floor Performance in Permutation Flowships
## 5 Conclusions and Further Research  
An extensive computational study has been carried out in order to analyse the links between several scheduling criteria in a flowshop and well-known shop floor performance measures. These results give some insights into the nature of these links, which can be summarised as follows. * Roughly speaking, we could divide the considered scheduling criteria into two big categories: those tightly related to any (some) shop floor performance measure, and those poorly related to  
Figure 2: Relative performance of the criteria for the different testbeds. SF performance. Among the later, we may classify \(CTV\) and \(\sum IT_{j}\). Nevertheless, this is not meant to say that these criteria are not useful. However, from a shop floor performance perspective, it may be interesting to investigate whether these scheduling criteria relate to other performance measures. Perhaps extending the analysis to a due date scenario might yield some positive answer. * Makespan matches (as theoretical predicted) throughput maximisation better than any other considered criteria. However, it turns out that differences between its minimisation and the minimisation of other criteria with respect to throughput are very small. Additionally, given the relatively poor performance of makespan with respect to \(ACT\), one might ask whether makespan minimisation pays off for many manufacturing scenarios in terms of shop floor performance as compared, e.g., to completion time or \(\sum ITH_{j}\) minimisation. A positive answer seems to be confined to these scenarios where costs associated to cycle time are almost irrelevant as compared to costs related to machine utilisation. The fact that this situation is not common in many manufacturing scenarios may lead to the lack of practical descriptions on the application of this criteria already discussed by [4]. * Completion time minimisation matches extremely well both work in process and average cycle time minimisation (the latter being theoretical predictable), better than any other criteria. In addition, the rest of the scheduling criteria perform much worse. Therefore, completion time minimisation emerges as a major criterion when it comes to increase shop floor performance. This empirical reasoning indicates the interest of the research on completion time minimisation rather than on other criteria, at least within the flowshop scheduling context. * The minimisation of idle time (including the heads) performs better than completion time with respect to throughput. However, its performance is substantially worse than completion time regarding \(ACT\) and \(WIP\). Hence, it seems an interesting criterion when throughput maximisation is the most important performance measure but work-in-process costs are not completely irrelevant. * With respect to the influence of the test-bed design on the results, there are noticeable differences between the overall results obtained in the correlated test-beds (LC-HC), and those obtained from the random test-bed. In general, the introduction of structured processing times seems to reduce the differences between the scheduling criteria. At a first glance, this means that random processing times make it difficult to achieve a good shop floor performance by the application of a specific scheduling criterion. It is widely know that random problems produce difficult instances in the sense that there were high differences between bad and good schedules (with respect to a given scheduling criterion), at least for the makespan criterion. In view of the results of the experiments, we can also assert that these also translate into shop floor performance measures. From these results, some aspects warrant future research:
* \(\sum ITH_{j}\) emerges as an interesting scheduling criterion, with virtues in between makespan and completion time. For most of the problem settings, it compares to makespan in terms of cycle time, and it outperforms total completion time in terms of throughput.