## 3 Results and Discussion
### Scenario of Products in RA
#### 3.2.1 Scenario of Products in EA  
For the results acquired in the scenario of products in the EA, there is a very slight difference in the scenarios of System State 0 and System State 1, but they yield considerably different results. The results shown in Figure 6 represent almost no difference in both of the standard logic approaches and the AOSR 2.0 Hybrid Logic as, in System State 0, there are no ADNs, which means products are only received at the warehouse with no product being delivered. In this case, the AOSR 2.0 planner algorithm has no opportunity to utilise its re-slotting strategy and shows almost the same pattern as the standard logics. From hours 1 through 3, as there are no products in the racks, all three strategies can easily find the capacity to store products within racks, and the extra products that exceed the total capacity are placed in EA. The difference can be noticed after the third hour, as from the fourth hour onwards, other than at the fifth hour, the zoning with FIFO logic has placed more products in EA because of its failure to incorporate consolidation logic like the zoning with fewest and AOSR 2.0's Hybrid Logic. In the fifth hour, the products appearing in ASNs have  
Figure 6: Comparison of Multiple Logics with AOSR 2.0 for Products in EA in State 0.  
different categories than those already stored in the racks, so the same number of products are placed in EA by each of the three strategies. The results in System State 1, as represented in Figure 7, clearly demonstrate the performance gap between the approaches. Because both the ASNs and ADNs are being received, AOSR 2.0 can utilise its re-slotting strategy when needed. In the first two hours, there is plenty of space and almost all products are easily stored within the racks, so the number of products in the EA is the same for all of the three strategies. However, after the second hour (and especially in the fourth hour), when the number of products is higher than capacity and when products with the same characteristics appear in upcoming ASNs and ADNs, the difference between AOSR 2.0 and standard strategies is quite visible. The AOSR 2.0 strategy manages to maintain a comparatively lower number of products in the EA throughout the random test scenarios, which can help reduce the issues of wandering or lost items and unmanaged inventory. The preference in the _Belief Base_ of the planner agent is to place a maximum number of products within the racks. However, when many similar products arrive, so that the total is greater than the maximum capacity of the warehouse for that particular product, the planner agent temporarily places some of the products in the EA. In parallel, it continuously checks with its _Knowledge Base_ for any updates about products to be shipped so that it can place the new products into racks rather than the EA and re-slot the products that will soon be needed in the EA from the racks. Then, when the delivery date arrives for the re-slotted products, they can be picked from the EA and space can be cleared for future possibilities. This can be observed during the third and fourth hours in Figure 7, when AOSR 2.0 places products in EA because the number of products in ASNs is much larger than the maximum capacity for that product batch, and it then re-slots the products from racks to the EA and places the newly arriving products into racks so that they do not need to be moved later and inventory can be managed more effectively. Additionally, in the sixth hour, when products with the same characteristics arrive in ASNs, both of the standard logics have placed a very high number of products in the EA, while AOSR 2.0 has placed the products from ADNs in the EA instead allowing the upcoming products to be placed in the racks. This is how AOSR 2.0's re-slotting strategy helps to maintain up to 107% fewer products in EA than the standard approaches. Our previous work [28] also supports the AOSR's performance efficiency overall. Figure 7: Comparison of Multiple Logics with AOSR 2.0 for Products in EA.