# Multi-AGV Scheduling under Limited Buffer Capacity and Battery Charging Using Simulation Techniques
## 4 Multi-AGV Scheduling Rules
### Experiment Results
Among the four alternatives, NCS (AAWT = 1213.55 (s)) and DCS (AAWT = 1217.17 (s)) are the best and worst ones; however, the difference between their performances was not large, which suggests that the charging station selection rule has limited impacts on the AWT. In contrast, the impact of the job selection rule is evident, as shown in Figure 8. For example, LDD (AAWT = 1094.67 (s)) and SDD (AAWT = 1103.41 (s)) rules produce a low AWT, indicating their usefulness for reducing the AWT. On the other hand, RJ (AAWT = 1322.74 (s)) and LQB (AAWT = 1347.19 (s)) rules show poor performances. In Figure 9, we can see that SDP (AAWT = 1213.47 (s)) and LDP (AAWT = 1217.80 (s)) are the best and worst rules for AGV selection, respectively. However, the deviation in their performances is not significant. Note that the AAWT was minimized under charging station selection rule = FCS, job selection rule = LDD, and AGV selection rule = SDP, as shown in Table 1. LDD is the best rule for job selection, as shown in Figure 8. Similarly, Figure 9 shows that SDP is the best AGV selection rule. On the contrary, FCS is not the best charging station rule, as shown in Figure 7. This means that AGV scheduling rules must be determined by conducting a multi-scenario simulation experiment. In other words, a combination of the best rules in Figures 7-9 does not guarantee optimal AGV scheduling. small compared to the overall work efficiency of AGVs. On the other hand, job selection rules determine the job order and priority of AGVs and are therefore directly linked to the overall work efficiency, which has a greater impact on the AWT. However, this does not mean that charging station selection rules and AGV selection rules are not important. These two rules remain important factors related to battery management in AGVs and are therefore essential to maintaining the efficiency of the overall system. In the context of energy efficiency or battery-related performance metrics, the criteria for selecting AGVs or charging stations may have greater significance than the rules governing job selection. Third, it is important to note that achieving the optimal combination of charging stations, job selection, and rules for AGV selection does not automatically ensure the most efficient AGV schedule. The average AWT of the entire scenario was recorded at 1084.33 (s), with the best outcome observed when the charging station selection rule was set to FCS, the job selection rule to LDD, and the AGV selection rule to SDP. However, Figures 7-9 indicate that LDD and SDP are preferable for job selection and AGV selection rules, respectively, whereas FCS is not the optimal selection. In other words, the combination of rules that seems optimal under specific conditions may not necessarily generalize well to different operational scenarios. These implications underscore the importance of an integrated approach that considers various variables and situations. In conclusion, we believe that it is desirable to evaluate the performance of AGV scheduling rules through multiple scenario experiments. This paper will provide practical insights into AGV scheduling. However, the proposed scheduling approach has some limitations. First, the types of scheduling rules are limited in this paper. For instance, only four types of charging station rules are used to define an experiment scenario. More diverse types of job selection, AGV selection, and charging station selection rules might be useful to optimize the scheduling policy. Second, the proposed scheduling approach is static in that it does not change the types of scheduling rules during the operation of the shopfloor. The performance measure might be further improved if the types of scheduling rules can be changed dynamically. Third, only one performance measure, the AWT, is considered in this paper, while various performance measures can be used to evaluate the performance of the AGV system. For instance, job tardiness, machine utilization, or battery charging-related measures can be more useful in some shopfloors.