賦能之智慧物流與3D視覺整合貨櫃裝載系統

提升貨櫃空間利用率與運輸安全是海運物流的重大挑戰。傳統人工排櫃常因空間估算失準導致卸貨重工。為此，本研究提出「智慧視覺化貨櫃裝載系統（IV-CLS）」，採用動態規劃與可行性修剪技術，縮減解空間以加速運算；並導入3D 視覺化模組實現數位雙生導引，彌平決策與現場疊櫃的資訊落差。實驗證實，IV-CLS 在嚴守物理堆疊限制下達成優異空間利用率。透過AI 與視覺化整合，本系統有效實現裝載標準化、成果可期性、成本最佳化與運輸安全。

Enhancing container space utilization and transportation safety is a major challenge in maritime logistics. Traditional manual stowage often causes unloading and rework due to inaccurate space estimation. To address this, this study proposes the Intelligent Visual Container Loading System (IV-CLS). It employs dynamic programming and feasibility pruning to reduce the search space and accelerate computation. Furthermore, a 3D visualization module is introduced to provide Digital Twin guidance, bridging the information gap between algorithmic decision-making and onsite execution. Experiments confirm that IV-CLS achieves excellent space utilization while strictly adhering to physical stacking constraints. By integrating AI and visualization, this system effectively realizes operational standardization, outcome predictability, cost optimization, and transportation safety.