Research on Port Container Congestion Relief Strategies under Multimodal Transport

The essence of container congestion at ports in multimodal transport systems is the systematic outbreak of the triple contradictions of rigid infrastructure, information silos and lagging systems. Research shows that the deep-seated root cause lies in the topological complexity of the multimodal transport network (multi-level coupling of sea, land and air), the spatio-temporal heterogeneity of traffic (sudden peaks and regional imbalances), and the conflict of main objectives (local optimization leading to global suboptimization). This paper proposes a "technology - system" dual-dimensional governance framework: At the technical level, a real-time mapping system for the physical and virtual aspects of the port is constructed through digital twins to achieve dynamic optimization of the storage yard. Researchers should adopt federated learning to overcome cross-agent data barriers and establish privacy-preserving collaborative decision-making mechanisms. Developers must reconstruct the document trust ecosystem using blockchain technology to ensure full-chain verifiability. Policymakers ought to design dynamic congestion pricing schemes and cross-domain governance protocols to equitably balance multi-stakeholder interests. Empirical evidence shows that digital twins have increased the turnover efficiency of storage yards by 40% and reduced the processing time of blockchain documents by 80%. The research provides a theoretical paradigm and technical path for breaking the "congestion - inefficiency" cycle.