A novel metaheuristic approach for AGVs resilient scheduling problem with battery constraints in automated container terminal

Abstract

As global concerns about carbon emissions mount, Automated Guided Vehicles (AGVs) have made a significant transition from reliance on petroleum fuel to predominantly utilizing electric power. However, in past port settings, the majority of Automated Guided Vehicle (AGV) control strategies have overlooked the impact of AGV charging and have not taken energy consumption into account. Furthermore, the AGV's electricity consumption is uncertain. Recognizing AGVs as the primary energy-consuming equipment in automated dockyards, this paper introduces a novel AGV resilient scheduling problem that integrates charging constraints and formulates a corresponding model that encompasses these limitations. Building upon established loading or unloading tasks, this model allocates AGV scheduling, including charging requests, to adhere to battery constraints and minimize AGV energy consumption costs. Moreover, a mathematical method based on Large Neighborhood Search (LNS) has been developed to address this issue. Finally, numerical experiments were conducted at a genuine large-scale automated port in China, meticulously analyzing the layout of charging areas, the establishment of charging thresholds, and the deployment of AGVs, thus highlighting the paramount significance of the operational framework of automated ports.