Battery-powered automated guided vehicles scheduling problem in automated container terminals for minimizing energy consumption

Abstract

Battery-Powered Automated Guided Vehicles (B-AGVs) are important equipment used to transfer containers between the seaside and the landside in automated container terminals. Due to their limited battery capacity, the B-AGVs require battery recovery when their battery reaches the threshold. However, the processing capacity of electrical battery swapping stations is limited, it is crucial to avoid congestion in swapping station. Considering that the scheduling problem of B-AGV in the terminal is time intensive, this paper proposes a set partitioning method based on breadth-first and depth-first search to solve the established mixed integer programming model. Combined with the operational characteristics of the terminal, this paper adopts the flexible pooling strategy to effectively matches the inbound and outbound containers to form dual-cycle operation of B-AGVs, which can reduce the computational complexity and thus improving the solution efficiency. In addition, the record-to-record travel algorithm is applied to improve the quality of the solution. Finally, the effectiveness of the proposed model and solution method is evaluated through numerical experiments. Besides, the applicability of the flexible pooling strategy to different container terminals is studied, and the impact of the number of B-AGVs and the capacity of swapping stations on the energy consumption of B-AGVs is investigated, and some managerial insights are given accordingly.