Energy Optimization of Large-Scale AGV Systems
Artikel i vetenskaplig tidskrift, 2020
We propose an efficient optimization method, which addresses several performance criteria such as makespan, maximum lateness, and the sum of tardiness for an automated guided vehicle (AGV) system, together with its energy consumption. We show that the most important factors in energy consumption of AGVs are their cruise velocities and traveled distances. We also demonstrate that optimizing the productivity-related performance criteria also reduces energy consumption through less traveled distance. It also allows for the reduction of the cruise velocity that leads to more energy savings. Our experiments demonstrate that the optimization method outperforms the existing traffic controller with respect to the performance criteria and reduces energy consumption. The proposed method can reduce the energy consumption by around 38%, while the values of makespan, lateness, and tardiness remain better than those obtained from the existing traffic controller. An important advantage of this paper is that the evaluations are based on
collected data from a real large-scale manufacturing plant.