Toward Full-Chain Collaboration: Optimizing Operational Scheduling in Four-Way Shuttle-Based Dense Storage Systems

Abstract

As a key support for high-density automated warehousing, the scheduling efficiency of the four-way shuttle system largely determines the overall throughput capacity. Aiming at the typical four-way shuttle system, this study carried out systematic research from four key dimensions: task allocation, path coordination, elevator coordination and dynamic disturbance response, combined with theoretical analysis and literature quantitative reasoning. The research system analyzes the efficiency bottleneck in the existing scheduling strategy. The results show that the experience-driven task allocation leads to serious resource competition; the independent path planning of each four-way shuttle cannot predict the conflict; elevator scheduling ignores global load balancing; static strategies are difficult to cope with dynamic disturbances. It is particularly important that these problems are intertwined, so that the actual throughput of the system only reaches 60% to 75% of the theoretical peak. Based on this, this study proposes targeted improvement measures, including task target clustering, path coordination based on time window, dynamic elevator priority scheduling, and event-driven online rescheduling. These strategies aim to promote the system from passive response to active collaboration, and provide theoretical support for improving the operational efficiency of high-density automated warehouses. The proposed framework not only lays a theoretical foundation for improving the operational efficiency of high-density automated warehouses, but also provides practical insights for practitioners to bridge the gap between theoretical design capacity and actual throughput in actual deployment.