# Simulation-Based Performance Analysis for a Novel AVS/RS Technology with Movable Lifts
## 5 Results and Discussion  
In this section, we provide the results of the simulations for the considered scenarios. We perform a \"steady-state\" analysis, by defining the \"warm-up\" periods in the designs. We observe that the average flow time per transaction reaches steady after 15 days run time by using the output analyser statistics in the software. We aim to complete our analyses for one month simulation runs. Hence, with the warm-up period, our replication runs are set for 45 days. To analyse the systems under highly utilized conditions, note that the models run for arrival rates so that we obtain larger than or equal to 95% utilization for the bottleneck devices (i.e., AGVs). Namely, the arrival rate is adjusted so that we obtain at least 95% average utilization for the AGVs. Table 3 shows the numerical results of the scenarios at 95% confidence intervals. In Arena software, output variability is reported via the half width, which is half of the 95 th percentile confidence interval for the related performance metric. From the results, we can draw a general conclusion that the warehouse design with novel AVS/RS/ML can produce reasonable throughput rates even there are few numbers of vehicles in the system designs. In both AVS/RS/ML system designs (i.e., with single I/O and two I/O points), it is observed that the bottleneck is always the AGVs (i.e., having higher utilization values than MLs). Since there are two MLs and two or three AGVs in the system, probably because the total travel distance of AGVs is usually longer than that of the MLs, they become bottleneck. The fact that the AGVs are bottleneck can also be revealed by comparison of the scenarios of 6 and 8 where it can be seen that when the third AGV is included in the system the throughput increases for more than 30%. The number of transactions that could be processed per month (\(\lambda\)) is always higher in two I/O points scenarios than in single I/O point scenarios regardless of the fact that the configuration of the racks and the number of MLs is the same. This is because the average operating time of an AGV per transaction (\(t_{o}\)) in two I/O points system design is higher than the other system design. Furthermore, note that the dwell point policy of both designs is different. In the single I/O design, AGV always returns to the I/O point after it discharges the transaction at the storage compartment whereas in the two I/O points design the AGV can wait inside the aisle. Therefore, in the single I/O design an AGV spends more time in travel than the other system design. Two I/O point design has an advantage in terms of throughput rate. However, it does not produce better average flow time per transaction \(\left(t_{f}\right)\) performance metric than the single I/O point system design. This is because under that design, we increase the mean arrival rate at the system, causing increased waiting time of transactions in queues--a transaction spends almost 95% of its \(t_{f}\) for waiting in the queue of AGV. The other inferences can be summarized as follows:  
* The studied novel AVS/RS/ML system provides reasonably good throughput rates under highly utilized levels of AGVs although the system works under a restrictive anti-collision algorithm. Once the operating policies and scheduling of transactions will be optimized, those values will be improved significantly. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Scenario** & **System** & **W** & **T** & **SC** & **N** & **Utilacv** & **Utilbnt** & **fy (s)** & **\(t_{o}\) (s)** &  
It can be observed from the results that even under highly utilization levels of AGVs, the two devices' utilizations are not that far away from each other as in the traditional SBS/RS. Furthermore, the novel system's design is flexible in the number of MLs and AGVs as well as in their velocities for further balancing of the device utilizations.