Transportation research, Part E. Logistics and transportation review2026,Vol.208Issue(Apr.) :1.1-1.40.DOI:10.1016/j.tre.2026.104707

Digital twin-based dynamic co-scheduling with AGV energy management in sea-rail intermodal automated container terminals

Li J. Chang D. Wen F. Moon I.
Transportation research, Part E. Logistics and transportation review2026,Vol.208Issue(Apr.) :1.1-1.40.DOI:10.1016/j.tre.2026.104707

Digital twin-based dynamic co-scheduling with AGV energy management in sea-rail intermodal automated container terminals

Li J. 1Chang D. 2Wen F. 3Moon I.4
扫码查看

作者信息

  • 1. Institute of Logistics Science and Engineering Shanghai Maritime University||Department of Industrial Engineering Seoul National University
  • 2. Logistics Engineering College Shanghai Maritime University
  • 3. Guangxi Bagui Engineering Supervision
  • 4. Department of Industrial Engineering Seoul National University||Institute of Logistics Science and Engineering Shanghai Maritime University
  • 折叠

Abstract

© 2026 Elsevier Ltd.To fully leverage the advantages of sea-rail intermodal transport, the automation upgrade of the railway center station (RCS) is essential for enabling seamless connectivity between the RCS and the terminal via automated guided vehicles (AGVs). This transformation introduces complex scheduling challenges for sea-rail intermodal automated container terminals (SRIACTs), including multi-directional container flows, coordination among diverse equipment, and AGV charging requirements with battery management. To address these challenges, this paper investigates the multi-equipment collaborative scheduling problem in SRIACTs with consideration of AGV charging. A mixed-integer programming model is formulated with sequencing, timing, and energy constraints, aiming to jointly minimize makespan and total charging time. To improve computational efficiency in large-scale cases, an improved genetic algorithm based on a decomposition-iteration framework is developed according to problem-specific features. Furthermore, to address operational uncertainties, a digital twin-based hybrid rescheduling framework is extended to enable real-time monitoring, disturbance detection, and rapid response to AGV status and battery levels, thereby enhancing system resilience and scheduling flexibility. Extensive numerical experiments are conducted to validate the effectiveness of the proposed algorithm and rescheduling framework. On this basis, comparative analyses are performed on bi-objective formulations and the flexible charging strategy. Additionally, sensitivity analyses examine the impacts of key factors, including objective weights, charging thresholds, rescheduling thresholds, and the number and layout of charging facilities. The findings provide valuable insights for terminal operators in formulating integrated scheduling strategies, optimizing AGV charging plans, and scientifically deploying charging infrastructure during the RCS automation process, thereby promoting sustainable and intelligent terminal operations.

Key words

Battery scheduling/Decomposition-iteration optimization/Digital twin/Multi-equipment co-scheduling/Sea-rail intermodal automated container terminal

引用本文复制引用

出版年

2026
Transportation research, Part E. Logistics and transportation review

Transportation research, Part E. Logistics and transportation review

ISSN:1366-5545
段落导航相关论文