Efficient Online Scheduling and Routing for Automated Guided Vehicles In Loop-Based Graphs
This addresses efficient AGV operations in manufacturing plants, but it appears incremental as it builds on existing scheduling and routing methods.
The paper tackled the problem of conflict-free online scheduling and routing for automated guided vehicles (AGVs) in loop-based graphs, proposing a loop-based algorithm that outperforms or matches other methods in solution quality with less computing time in experiments using theoretical and real instances.
Automated guided vehicles (AGVs) are widely used in various industries, and scheduling and routing them in a conflict-free manner is crucial to their efficient operation. We propose a loop-based algorithm that solves the online, conflict-free scheduling and routing problem for AGVs with any capacity and ordered jobs in loop-based graphs. The proposed algorithm is compared against an exact method, a greedy heuristic and a metaheuristic. We experimentally show, using theoretical and real instances on a model representing a real manufacturing plant, that this algorithm either outperforms the other algorithms or gets an equally good solution in less computing time.