Open Access

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

Prof. Suleiman Ibrahim Shelash Mohammad Mohammad

Electronic Marketing and Social Media, Faculty of Economic and Administrative Sciences, Zarqa University, Zarqa 13115, Jordan

Badrea Al Qraini Qraini

Department of Business Administration, College of Business and Economics, Qassim University, Qassim, Saudi Arabia.

Sultan Alaswad Alenazi Alenazi

Department of Marketing, College of Business, King Saud University, Riyadh 11362, Saudi Arabia

Asokan Vasudevan Vasudevan

Faculty of Business and Communications, INTI International University, Nilai 71800, Malaysia Faculty of Management, Shinawatra University, 99 Moo 10, Bangtoey, Samkhok 12160, Thailand Business Administration and Management, Wekerle Business School, Jázmin u. 10, 1083 Budapest, Hungary

Anber Abraheem Shelash Shelash

Digital Marketing Department, Faculty of Administrative and Financial Sciences, University of Petra, Amman 11196, Jordan.

Imad Ali Ali

Operations Supply Chain & IQAC, GNIOT Institute of Management Studies, Greater Noida, Uttar Pradesh, India.

DOI: https://doi.org/10.36956/sms.v7i3.2471

Received: 16 July 2025; Published: 9 September 2025

Copyright © 2025 Prof. Suleiman Ibrahim Shelash Mohammad Mohammad, Badrea Al Qraini Qraini, Sultan Alaswad Alenazi Alenazi, Asokan Vasudevan Vasudevan, Anber Abraheem Shelash Shelash, Imad Ali Ali. Published by Nan Yang Academy of Sciences Pte. Ltd..


Abstract

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.

Keywords: Decarbonization, Offshore Logistics, Multi-Echelon Supply Chain, Emission Optimization, Marine Fuel Alternatives


References

Online ISSN: 2661-3158, Published by Nan Yang Academy of Sciences Pte. Ltd.