Cross-docking is a logistics method operated in a freight terminal to achieve efficiency by consolidating and transferring freight directly from an inbound dock to an outbound dock in less than 24 hours with no or limited storage. To this end, cross-docking needs perfect coordination of incoming and outgoing flows on logistics platforms under uncertain conditions.
To achieve efficiency against uncertainty in cross-docking processes, practitioners and researchers use simulation as a handy tool to test the performance of their built systems under different operating conditions to prevent issues before they are encountered. To this end, three main simulation modeling techniques are used in the cross-docking domain: discrete-event simulation (DES), multi-agent-based simulation (MAS), and hybrid models (i.e., integration of DES and MAS).
This study develops a real-time multi-agent truck scheduling model for single inbound-single outbound cross-docking for fast synchronization of inflows and outflows. The proposed model exploits the autonomous, reactive, and distributed responsibility characteristics of the multi-agent systems to achieve shared computation and provide flexible responses to dynamic events.
This type of model is novel in the cross-docking literature for scheduling both inbound and outbound trucks. The responsiveness of the proposed model is evaluated by employing a combination of different traffic levels based on truck arrival times. Furthermore, various truck-to-door assignment strategies are implemented to achieve the best performance based on key performance indicators such as the average stock level, the number of late pallets, the pallet delay, and the outbound truck fill rate.
This study shows that multi-agent-based approaches are effective techniques for solving real-time truck scheduling problems for cross-docking. However, the literature review conducted revealed that the application of the MAS to real-time truck scheduling still needs to be explored. This study addresses this issue by proposing a multi-agent-based hybrid model for real-time scheduling of both inbound and outbound trucks and internal cross-docking operations.
The main findings of this study are as follows:
- The first major finding is the proof of concept for the use of a hybrid model (of MAS and DES) for real-time truck scheduling in cross-docks.
- The second major finding involves the in-depth analysis of different truck scheduling strategies that are easy to apply in a real-time manner, subject to different traffic levels.
This study confirms the performance of the proposed multi-agent-based hybrid model for the studied single-inbound and single-outbound door cross-dock. However, it also has some limitations that help researchers draw several perspectives for future studies.