Impact of the Deadlock Handling Method on the Energy Efficiency of a System of Multiple Automated Guided Vehicles in a Production Environment Described as a Square Topology

Efficient control a system of multiple Automated Guided Vehicles (AGVs) is crucial for modern intralogistics given the growing importance of energy consumption and operating costs. This study investigates the impact of two deadlock handling methods: Chain Of Reservations (COR) and Structural On-line Control Policy (SOCP), on the energy efficiency and performance of AGV systems operating in a production environment described as square topology. A simulation model developed in FlexSim implemented both methods using real AGV data on electricity consumption during various tasks. The analysis also discusses the adopted battery charging strategy. Simulation experiments combined each deadlock handling method with two path-planning strategies: shortest path and fastest path. Pseudocode algorithms for determining these paths in an environment described as square topology are provided. System performance was evaluated across a wide range of AGV fleet sizes, focusing on key indicators such as total energy consumption, time to complete transportation tasks, and AGV utilization rate. Multi-criteria optimization reduced the problem to two conflicting objectives: energy consumption and completion time, with Pareto fronts generated for each configuration studied. The results demonstrate that both the deadlock handling strategy and the selected pathfinding algorithm significantly influence the evaluation criteria. This original research integrates solving the deadlock problem with controlling energy efficiency and task completion time in structured transportation environments that are not deadlock-free by design.