بهینه سازی چند هدفه برای توازن کانتینرهای خالی در شبکه بنادر هاب و فیدر با رویکرد پایداری در حمل و نقل دریایی

زیار, الهام; امیری, بابک; صاحبی, هادی

doi:10.61882/jii.2.4.320

بهینه سازی چند هدفه برای توازن کانتینرهای خالی در شبکه بنادر هاب و فیدر با رویکرد پایداری در حمل و نقل دریایی

نوع مقاله : مقاله پژوهشی

نویسندگان

الهام زیار ¹

بابک امیری ²

هادی صاحبی ²

¹ گروه لجستیک و زنجیره تامین، دانشکده صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

² گروه سیستم های هوشمند، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

10.61882/jii.2.4.320

چکیده

صنعت حمل‌ونقل دریایی، به‌عنوان ستون فقرات تجارت جهانی، با چالش‌هایی چون عدم تعادل کانتینرهای خالی، آلودگی زیست‌محیطی و ناکارآمدی عملیاتی در بنادر مواجه است. این مقاله با تمرکز بر شبکه حمل‌ونقل کانتینری مبتنی بر ساختار هاب و فیدر، یک مدل ریاضی ترکیبی را برای بهینه‌سازی همزمان سه هدف اصلی ارائه می‌دهد: سودآوری اقتصادی، کاهش عدم تعادل کانتینرهای خالی، و ارتقاء پایداری زیست‌محیطی. در این مدل، نقش کشتی‌های لاینر و فیدر، مسیرهای دریایی، و بنادر هاب، فیدر و ستلایت با جزئیات بررسی شده‌اند. برای اعتبارسنجی مدل، یک مطالعه‌ موردی بر مسیر بنادر خاورمیانه و شرق آسیا با استفاده از نرم‌افزار GAMS انجام شد. نتایج نشان‌دهنده کاهش قابل‌توجه در عدم توازن کانتینرهای خالی در طی سه دوره زمانی و نیز بهینه‌سازی هم‌زمان پارامترهای اقتصادی و زیست‌محیطی هستند. تحلیل حساسیت مدل نیز بیانگر نقش کلیدی ظرفیت کشتی در بهبود عملکرد سیستم است، اگرچه این عامل به تنهایی کافی نبوده و نیازمند مدیریت جامع در سطوح مختلف است.

کلیدواژه‌ها

Empty container balance

Sustainability

Maritime logistics

عنوان مقاله English

Sustainable Multi-Objective Optimization for Empty Container Balancing in Maritime Hub-and-Feeder Network

نویسندگان English

Elham Ziar ¹

Babak Amiri ²

Hadi Sahebi ²

¹ School of Industrial Engineering, Iran University of Science &amp; Technology, Tehran, Iran

² School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran

چکیده English

The maritime transport industry, often referred to as the backbone of global trade, plays a pivotal role in facilitating the movement of goods across international markets. Despite its importance, the industry is plagued by several persistent challenges that hinder its operational efficiency and sustainability. Among the most critical are the imbalance of empty containers, environmental degradation due to emissions and fuel consumption, and inefficiencies in port operations. These issues collectively pose serious implications for cost management, environmental impact, and service reliability. In an effort to address these concerns, this paper proposes a novel multi-objective mathematical model that seeks to optimize three primary goals in an integrated manner: maximizing economic profitability, minimizing the imbalance of empty containers, and enhancing environmental sustainability. The model is designed to reflect real-world shipping dynamics, incorporating the interactions between liner and feeder ships, multiple sea routes, and various types of ports, including hub, feeder, and satellite ports. To demonstrate the practical applicability and robustness of the model, a case study is conducted on a representative shipping network involving selected ports in the Middle East and East Asia. The model is implemented using the General Algebraic Modeling System (GAMS), and its outputs are analyzed across three distinct time periods. Results indicate a significant reduction in the number of empty containers, along with concurrent improvements in both cost-effectiveness and environmental performance indicators. Additionally, a comprehensive sensitivity analysis underscores the pivotal role of ship capacity in influencing system outcomes. However, it also reveals that improvements in a single dimension are insufficient for holistic system optimization. Effective and sustainable management of maritime transport requires a multidimensional strategy that balances economic, environmental, and operational factors. The proposed model offers valuable insights for decision-makers aiming to improve the resilience and sustainability of global shipping networks.

کلیدواژه‌ها English

توازن کانتینرهای خالی

پایداری

لجستیک دریایی

[1] Lam L, Iskounen A. Feeder ports, Inland ports and Corridors-Time for a closer look. HTG Yearbook 2010. 2010:19-23.
[2] Yang L, Zheng J, Wang J. Hub port location and routing for a single-hub feeder network: Effect of liner shipping network connectivity. Transport Policy. 2025;160:212-27.
[3] Huang X, Chen H, Zhang J, Wang D, Chen J, Luo JX. Robust optimization model of container liner routes in feeder line network. Transport. 2024;39(1):13-24.
[4] Humang WP, Utomo DP, Putra H, Arianto D, Pujiwat R, Upahita DP, Fitriana N, Salsabilla MA, Hendra YN, Nurhidayat AY, Putri MN. Hub-and-spoke network design to optimize government subsidy costs for maritime transportation in Indonesia. Sustainable Futures. 2025;9:100602.
[5] Tikani H, Honarvar M, Mehrjerdi YZ. Joint optimization of star P-hub median problem and seat inventory control decisions considering a hybrid routing transportation system. International Journal of Supply and Operations Management. 2016;3(3):1.
[6] Golmohammadi AM, Abedsoltan H. A Bi-objective Model of Many-To-Many Hub Vehicle Location-Routing Problem by Considering Hard Time Window and Vehicle-Cost Balancing. Iranian Journal of Operations Research. 2023;14(2):156-67.
[7] Tikani H, Ramezanian R, Setak M, Van Woensel T. Hybrid evolutionary algorithms and Lagrangian relaxation for multi-period star hub median problem considering financial and service quality issues. Engineering Applications of Artificial Intelligence. 2021;97:104056.
[8] Lee S, Moon I. Robust empty container repositioning considering foldable containers. European Journal of Operational Research. 2020;280(3):909-25.
[9] Song DP, Dong JX. Cargo routing and empty container repositioning in multiple shipping service routes. Transportation Research Part B: Methodological. 2012;46(10):1556-75.
[10] Chen R, Dong JX, Lee CY. Pricing and competition in a shipping market with waste shipments and empty container repositioning. Transportation Research Part B: Methodological. 2016;85:32-55.
[11] Song DP, Xu J. An operational activity-based method to estimate CO2 emissions from container shipping considering empty container repositioning. Transportation Research Part D: Transport and Environment. 2012;17(1):91-6.
[12] Meng Q, Wang S. Liner shipping service network design with empty container repositioning. Transportation Research Part E: Logistics and Transportation Review. 2011;47(5):695-708.
[13] Shintani K, Konings R, Imai A. Combinable containers: A container innovation to save container fleet and empty container repositioning costs. Transportation Research Part E: Logistics and Transportation Review. 2019;130:248-72.
[14] Kuzmicz KA, Pesch E. Approaches to empty container repositioning problems in the context of Eurasian intermodal transportation. Omega. 2019;85:194-213.
[15] Luo T, Chang D. Empty container repositioning strategy in intermodal transport with demand switching. Advanced Engineering Informatics. 2019;40:1-3.
[16] Abdelshafie A, Rupnik B, Kramberger T. Simulated global empty containers repositioning using agent-based modelling. Systems. 2023;11(3):130.
[17] Wang W, Diao C, He W, Jin Z, Yang Z. Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters. Journal of Marine Science and Engineering. 2025;13(1):159.
[18] Fu F, Ji M. Robust inventory planning of empty containers in intermodal transportation considering port congestion. Computers & Industrial Engineering. 2025:111233.
[19] Cai J, Huang Y, Diao C, Jin Z. Joint Optimization of Multi-Period Empty Container Repositioning and Inventory Control Based on Adaptive Particle Swarm Algorithm. Journal of Marine Science and Engineering. 2025;13(6):1113.
[20] Liang J, Ma Z, Wang S, Liu H, Tan Z. Dynamic container slot allocation with empty container repositioning under stochastic demand. Transportation Research Part E: Logistics and Transportation Review. 2024;187:103603.
[21] Feng X, Wang Z, Wang Y, Yin W, Chao Y, Ye G. Improving resilience in an intermodal transport network via bulk cargo transport coordination and empty container repositioning. Ocean & Coastal Management. 2024;248:106970.
[22] Xiang X, Wang Z, Gong L, Jia S, Liu X, Liu M. Integrated optimization of vessel dispatching and empty container repositioning considering turnover time uncertainty. Computers & Industrial Engineering. 2024;197:110566.
[23] Ziar E, Amiri B, Sahebi H, Bashiri M. Balancing empty containers at ports: A bi-level programming approach for sustainable maritime logistics. Journal of Cleaner Production. 2025:145649.
[24] Wang S, Wang X, Han Y, Wang X, Jiang H, Duan J, Hua R, Zhang Z. Decarbonizing in maritime transportation: Challenges and opportunities. Journal of Transportation Technologies. 2023;13(2):301-25.
[25] Russo M, Carvalho D, Jalkanen JP, Monteiro A. The future impact of shipping emissions on air quality in Europe under climate change. Atmosphere. 2023;14(7):1126.
[26] Degiuli N, Farkas A, Martić I, Gospić I. GHG abatement potential due to the implementation of slow steaming. Casopis Pomorskog Fakulteta Kotor-Journal of Maritime Sciences. 2022;23(1):2022.
[27] Livaniou S, Papadopoulos GA. Liquefied natural gas (LNG) as a transitional choice replacing marine conventional fuels (heavy fuel oil/marine diesel oil), towards the era of decarbonisation. Sustainability. 2022;14(24):16364.
[28] Tijan E, Agatić A, Jović M, Aksentijević S. Maritime national single window—a prerequisite for sustainable seaport business. Sustainability, 11 (17), 4570 [Internet]. 2019
[29] Pavlinović M, Račić M, Mišura A. The importance of digitalization for sustainable development of maritime industry. Transactions on maritime science. 2023;12(02).
[30] Eom JO, Yoon JH, Yeon JH, Kim SW. Port digital twin development for decarbonization: A case study using the Pusan Newport International Terminal. Journal of marine science and engineering. 2023;11(9):1777.
[31] Camargo-Díaz CP, Paipa-Sanabria E, Zapata-Cortes JA, Aguirre-Restrepo Y, Quiñones-Bolaños EE. A review of economic incentives to promote decarbonization alternatives in maritime and inland waterway transport modes. Sustainability. 2022;14(21):14405.
[32] Christodoulou A, Cullinane K. Identifying the main opportunities and challenges from the implementation of a port energy management system: A SWOT/PESTLE analysis. Sustainability. 2019;11(21):6046.
[33] Ekmekçioğlu A, Ünlügençoğlu K, Çelebi UB. Container ship emission estimation model for the concept of green port in Turkey. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment. 2022;236(2):504-18.
[34] Golmohammadi AM, Abedsoltan H, Goli A, Ali I. Multi-objective dragonfly algorithm for optimizing a sustainable supply chain under resource sharing conditions. Computers & Industrial Engineering. 2024;187:109837.
[35] Ziar E, Seifbarghy M, Bashiri M, Tjahjono B. An efficient environmentally friendly transportation network design via dry ports: a bi-level programming approach. Annals of Operations Research. 2023;322(2):1143-66.
[36] Rashidian F. A bi-objective integrated model for blood supply chain network design with a product quality improvement approach. Industrial Innovations. 2023;1(3):255-270. [In Persian]. doi:https://doi.org/10.61186/jii.1.3.255
[37] Saraabadani F, Bazoukar R, Rashidian F. Development of a green supplier selection model with the objective of optimizing selection criteria and considering incremental discounts. Industrial Innovations. 2024;2(1):1-21. [In Persian]. doi:https://doi.org/10.61186/jii.2.1.1
[38] Torabi SA, Hassini E. An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy sets and systems. 2008;159(2):193-214.