Decarbonizing Marine Logistics: Multi-Echelon Green Supply Chain Models for Offshore Vessel Networks

This study addresses the critical need for decarbonization in offshore marine logistics by developing an integrated modeling framework to support low-emission operations across complex, multi-echelon vessel networks. It focuses on port-to-platform supply chains serving offshore wind farms, oil rigs, and floating logistics hubs. A hybrid analytical approach was adopted, combining Mixed-Integer Linear Programming (MILP) for optimizing emission-minimizing routing, Discrete-Event Simulation (DES) to evaluate offshore scheduling performance under variability, and a Multi-Criteria Decision Analysis (MCDA) model using AHP-TOPSIS to rank alternative marine fuel types. Monte Carlo simulation was also employed to assess cost and delivery fluctuations across uncertain operational scenarios. Data inputs were compiled from real-world offshore fleet specifications, port emissions records, and marine fuel technology benchmarks. MILP-based network flow optimization reduced CO₂ emissions by 22% while maintaining service reliability across all demand points. DES simulations revealed congestion-driven scheduling delays during peak vessel utilization. MCDA analysis ranked bio-LNG and hydrogen propulsion systems as optimal choices based on emission, cost, and availability trade-offs. Hypothesis testing confirmed significant relationships between fuel type, network structure, and emission performance. The study demonstrates how multi-echelon logistics planning, integrated with emissions-based modeling, can facilitate environmentally responsible marine supply chain design. The framework offers practical guidance for offshore fleet managers, port authorities, and policy regulators aiming to align operational efficiency with decarbonization objectives under IMO and EU directives.