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Design of flexible truck appointment system based on machine learning approach

Author

Listed:
  • Maurício Randolfo Flores da Silva
  • Enzo Morosini Frazzon
  • Vanina Macowski Durski Silva

Abstract

Smart ports are adopting Industry 4.0 concepts and technologies so that more efficient and resilient operations emerge. Real-time data acquired from smart technologies can be deployed to anticipate disruptions and to actively manage hinterland port flows. In this context, the flexible rescheduling of truck flows in response to unpredictable circumstances allows for congestion mitigation and reduced cycle time. This paper investigates the literature regarding smart ports, scheduling methods, and machine learning approaches, in order to propose a conceptual model for flexible truck appointment systems, able to consider a continuous stream of real-time data from smart technologies to identify disruptive events and to dynamically reschedule truck appointments, ensuring the synchronisation of hinterland port truck flows.

Suggested Citation

  • Maurício Randolfo Flores da Silva & Enzo Morosini Frazzon & Vanina Macowski Durski Silva, 2024. "Design of flexible truck appointment system based on machine learning approach," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 48(2), pages 244-266.
    • Handle: RePEc:ids:ijlsma:v:48:y:2024:i:2:p:244-266
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