A Comparative Study of Routing Schemes in Discrete-Event Simulation Models for AGV Systems

With advancements in smart factory and IoT technologies, Automated Guided Vehicle (AGV) and Autonomous Mobile Robot (AMR) fleets continue to grow, and discrete-event simulation (DES) has become a key tool for operational design. However, DES-based studies tend to focus on scheduling and dispatching, while the routing scheme by which a vehicle determines its path during travel is often overlooked or left at the default shortest-path setting, despite it directly shaping how congestion and blocking arise. To address this gap, this study treats the routing scheme itself as the object of analysis and—within a commercial DES under a common layout, fleet, and demand—implements and compares three schemes: a static scheme (SR) and two dynamic schemes that avoid occupied segments during travel. This includes Distributed Dynamic Routing (DDR), a greedy control-point scheme, and Centralized Dynamic Routing (CDR), a Min-Cost Flow scheme. Rather than proposing a new routing algorithm, the study contributes a controlled comparison that isolates the extent to which the routing scheme alone changes the performance reported by a commercial DES, together with a reproducible way of embedding mid-travel rerouting in such a tool. Experiments on a unidirectional-path AGV system in FlexSim, covering twelve combinations of fleet size and load/unload time with 1000 runs each, show that DDR and CDR reduce the blocked time of the static default by a median of 97.8% and 73.5%, respectively, while the median change in makespan remains below 2%; these reductions come at the cost of 7.2% and 37.2% longer travel distances, respectively, and the preferable dynamic scheme depends on the fleet size and the load/unload time. These results demonstrate that the routing scheme is a decisive lever for both DES model fidelity and the performance of the AGV systems they represent, and that it should be selected and reported explicitly rather than left at the default setting.