Strategic evolution of port oil depot scheduling: From local optimization to integrated low-carbon energy hubs

Abstract

As global energy systems undergo a profound transition towards sustainability and resilience, the strategic role of port oil depots has evolved from mere logistical nodes to critical hubs governing energy security and low-carbon integration. This study conducts a systematic analysis of 637 publications (2014–2025) to map the strategic evolution of scheduling optimization in this domain. The findings reveal a clear paradigm shift: from isolated, single-point efficiency optimization towards integrated “ship-shore-pipeline” synergy, aimed at resolving systemic bottlenecks such as “vessels waiting for tanks”. Concurrently, decision-making objectives have expanded to encompass a multi-dimensional trade-off among economic efficiency, carbon emissions, and system resilience, reflecting the influence of global “dual carbon” goals. Methodologically, mixed integer linear programming (MILP) dominates for modeling complex physical constraints, while the integration of artificial intelligence with operations research (OR-AI) emerges as a key enabler for handling uncertainty. Spatially, research leadership is concentrated in demand-driven China and technology-driven the US, yet cross-border collaboration remains limited. By constructing a “scenario-objective-method” framework, this study deciphers the knowledge architecture and evolutionary trajectory, concluding with strategic priorities for future research-including dynamic resilient scheduling, multi-energy flow coupling, and full-lifecycle green decision-making-to guide the development of next-generation intelligent and sustainable port energy hubs.