## 3 Results and Discussion
### Scenario of Products in Racks  
Figure 2 represents the results taken from System State 0. The results reflect the difference between the tested approaches for the applied test dataset for a full routine day. The number of transactions and iterations are divided into hours (represented on the \(x\)-axis) and the number of products being shipped or delivered to the warehouse (represented on the \(y\)-axis). The graph reflects that there is no major difference in the two standard warehousing logics, zoning with FIFO logic and zoning with fewest logic. Although the results generated by AOSR 2.0 represent almost the same pattern, the situation is 10-15% better than the other two approaches as it stores more products in the racks than either of the other two strategies, which is considered a high-performance efficiency metric in a warehouse environment [33]. Nonetheless, all three curves move down after the 6 th hour because they reach capacity in the constrained environment. AOSR 2.0, in this scenario, follows the same trend as the other techniques (with better performance than the others because it follows the strategy to keep the minimum possible number of products at the product receiving area) as it utilises its hybrid logic and is not offered a situation where its re-slotting strategy can be utilised since no delivery operations are performed. In System State (1) the performance improvement of AOSR 2.0 over the other techniques is more easily noticed, i.e., in Figure 3.  
Figure 3 provides a comparison of the two standard approaches with the hybrid strategy of AOSR 2.0. As can be seen from the graph, for the first 4 hours, both zoning with FIFO logic and zoning with fewest logic have only marginal differences because both of the approaches follow the same pattern of leaving one-quarter of the products in a RA. The main reason for this is because these standard approaches use a manual method of sorting the received products and hence identifying the proper location takes more time [33]. However, the AOSR 2.0 strategy is based on the enterprise integration concepts of the AOSF framework and considers the ASNs or ADNs prior to the arrival of products. Hence, the proactive nature of the AOSR 2.0 strategy already reduces the time taken to identify and place products. After the fourth hour, the performance gap and difference between the AOSR 2.0 strategy and the standard approaches can easily be noticed as AOSR 2.0 utilises its hybrid strategy for product re-slotting to organise space and increase availability for new products. This allows AOSR 2.0 to maintain almost 60% more  
Figure 3: Comparison of Multiple Logics with AOSR 2.0 for Products in Racks State 1.  
Figure 2: Comparison of Multiple Logics with AOSR 2.0 for Products in Racks in State 0.  
products in racks than the other approaches. For the fifth hour, a difference can be seen between the two standard approaches; zoning with fewest logic performed comparatively better than zoning with FIFO logic because it tried to consolidate the space to make more availability for new products to be stored within racks. As the AOSR 2.0 strategy utilises a combination of these approaches, it is more successful and yields better results than the other two individually. A clear performance difference can be seen during the sixth hour, which ultimately reduces for the seventh and eighth hour as the number of total products is reduced in upcoming shipment and delivery notices.