Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.0
2.8
Journals
JMSE
Special Issues
Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental...
share announcement

Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 15 July 2026 | Viewed by 1662

Special Issue Editors

Prof. Dr. Chao Mi

E-Mail Website
Guest Editor
College of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: port equipment automation; intelligent traffic equipment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Guangnian Xiao

E-Mail Website
Guest Editor
School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
Interests: intelligent transportation; green shipping; sustainable transportation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, global maritime trade is operating within a complex and dynamic macro-environment. Over 80% of global trade relies on maritime transport, and trade volumes continue to rise. UNCTAD notes that global maritime trade reached 12.3 billion tons in 2023, grew by 2.4% to 12.6 billion tons in 2024, and is projected to reach approximately 12.9 billion tons in 2025. In this context, sustainable shipping, port intelligence, and marine environmental engineering have become critical drivers for the green transformation of the ocean economy. Simultaneously, with the interconnectivity of global supply chains, the intelligent and green transformation of ports and land transport is increasingly vital to address climate change, supply chain disruptions, and efficiency challenges.

Based on this, JMSE is inviting Prof. Chao Mi and Prof. Guangnian Xiao to establish a Special Issue entitled "Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering". This Special Issue aims to explore how technological innovation and engineering solutions can enhance maritime operational efficiency, minimize environmental impact, and promote smarter, more sustainable port management and international supply chain integration. We invite scholars and industry experts worldwide to share their research findings and contribute valuable insights to the sustainable development of the global shipping, port, and supply chain industries.

Historically, maritime transport has evolved from traditional labor-intensive operations to the era of containerization and, more recently, into the age of digitalization and automation (Industry 4.0). While early developments focused primarily on scale and speed to meet growing trade demands, the focus has shifted significantly in the last decade. The industry is now transitioning from purely economic-driven logistics to a complex ecosystem that prioritizes environmental sustainability and ecological safety. This evolution has given rise to the integration of Marine Environmental Engineering with port operations, marking a new historical stage where smart technologies are not just used for efficiency, but also for pollution control, decarbonization, and ecosystem protection. This Special Issue builds upon this historical trajectory, addressing the urgent need to merge legacy infrastructure with modern intelligence and green engineering standards.

Current cutting-edge research lies at the intersection of digitalization, decarbonization, and environmental resilience. We are witnessing a surge in studies focusing on Digital Twins for port management, which allow for real-time monitoring of both logistical flows and environmental parameters (such as water quality and emissions). In the realm of Marine Environmental Engineering, advanced research includes the development of eco-friendly dredging techniques, noise reduction technologies for ships, and ballast water treatment systems driven by AI optimization. Furthermore, the application of Blockchain and Big Data for transparent, low-carbon supply chain management represents a significant frontier. Scholars are also exploring the engineering challenges of retrofitting ports for alternative fuels (e.g., hydrogen, ammonia) and designing climate-resilient maritime infrastructure to withstand extreme weather events.

What kind of paper we are looking for:

This Special Issue will cover review articles and original research on "Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering". We will focus on key issues such as intelligent operations management, smart equipment in maritime and port operations, sustainable shipping strategies, innovative practices in port management, marine environmental engineering applications, and the optimization and green transformation of international supply chains. Our goal is to provide useful ideas and solutions for the industry, including, but not limited to, the following topics:

  1. Climate Change and Carbon Reduction Pathways in Shipping: Research on the impact of climate change on shipping and how the industry can achieve carbon reduction goals through technical innovation and policy guidance.
  2. Port Digital Transformation and Smart Development: Analysis of digital and intelligent technologies in port management to improve operational efficiency and service quality.
  3. Green Port Development and Marine Environmental Engineering: Case studies on green and low-carbon transitions in ports, discussing engineering measures to reduce environmental impact, manage waste, and promote green port construction.
  4. Collaborative Innovation in Shipping and Ports: Analysis of collaboration between shipping and port sectors in technology innovation and service optimization.
  5. Intelligent Operations Management in Maritime and Ports: Exploring the integration of digital technologies and AI to enhance operational efficiency and decision-making capabilities.
  6. Smart Equipment in Maritime and Port Operations: Investigating advancements in smart maritime and port equipment, including automated vessels and intelligent cargo handling systems.
  7. International Maritime Supply Chain Management: Exploring optimization strategies for global maritime supply chains, including resilience, risk management, and multimodal integration.
  8. Port Intelligence and Green Transformation: Analyzing the application of AI, IoT, and big data in smart ports, as well as green operations such as renewable energy use.
  9. Intelligence and Greening of Port and Land Transport: Research on the seamless connection between ports and land transport (rail, road), including smart traffic systems and electrification strategies.
  10. Marine Environmental Engineering Technologies: Engineering solutions for pollution control, marine ecological protection, and sustainable infrastructure in maritime settings.

Prof. Dr. Chao Mi
Prof. Dr. Guangnian Xiao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable maritime transport
  • port intelligence
  • marine environmental engineering
  • supply chain management
  • green shipping
  • carbon reduction
  • digital transformation
  • smart logistics
  • multimodal transport

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

29 pages, 3734 KB  
Article
Q-Learning-Based Sailing Speed Optimization for Ocean-Going Liners Under the EU ETS: Considering Shipper Satisfaction
by Tong Zhou, Tiantian Bao, Yifan Liu and Chuanqiu Zhang
J. Mar. Sci. Eng. 2026, 14(9), 848; https://doi.org/10.3390/jmse14090848 - 30 Apr 2026
Viewed by 210
Abstract
With the formal inclusion of the shipping industry in the European Union Emissions Trading System (EU ETS), the speed optimization of ocean-going container ships must simultaneously balance operating costs, incorporating carbon emission costs and shipper satisfaction with transportation timeliness. Taking ocean-going container liner [...] Read more.
With the formal inclusion of the shipping industry in the European Union Emissions Trading System (EU ETS), the speed optimization of ocean-going container ships must simultaneously balance operating costs, incorporating carbon emission costs and shipper satisfaction with transportation timeliness. Taking ocean-going container liner routes as the research object, this paper establishes a ship navigation resistance model based on meteorological and hydrological conditions, and constructs a route segmentation mechanism and a ship fuel consumption model on this basis. The spatially differentiated carbon accounting rules of the EU ETS are introduced, a fuzzy membership function is adopted to quantify shipper satisfaction, and a Q-learning-based solution algorithm for ship speed optimization that balances operating costs and shipper satisfaction is designed. Numerical experiments on a 20,150 Twenty-foot Equivalent Unit (TEU) container ship demonstrate that the proposed framework reduces total operating costs by 5.56%, EU ETS carbon compliance costs by 18.72%, and total voyage carbon emissions by 11.01% compared with the conventional constant-speed strategy. Meanwhile, the algorithm can spontaneously form an optimal speed strategy adapted to meteorological conditions and policy rules. Through parameter sensitivity analysis, this paper further extracts management implications for liner-operating companies. Full article
(This article belongs to the Special Issue Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering)
►▼ Show Figures

Figure 1

29 pages, 4475 KB  
Article
Seamless Task Scheduling for Vehicle-Crane Coordination in Container Terminals: A Spatio-Temporal Optimization Approach
by Xingyu Wang, Xiangwei Liu, Jintao Lai, Weimeng Lin, Qiang Ling, Yang Shen, Ning Zhao and Jia Hu
J. Mar. Sci. Eng. 2026, 14(7), 614; https://doi.org/10.3390/jmse14070614 - 26 Mar 2026
Viewed by 481
Abstract
Task scheduling for vehicle–crane coordination is crucial for the operational efficiency of electrified automated container terminals (ACTs). However, under fully shared dispatching, existing studies rarely capture how charging-induced capacity fluctuations disrupt bidirectional service–arrival matching and propagate service-window shifts. To address this gap, this [...] Read more.
Task scheduling for vehicle–crane coordination is crucial for the operational efficiency of electrified automated container terminals (ACTs). However, under fully shared dispatching, existing studies rarely capture how charging-induced capacity fluctuations disrupt bidirectional service–arrival matching and propagate service-window shifts. To address this gap, this study proposes a comprehensive spatio-temporal optimization approach. Firstly, a bi-objective model is established to minimize service–arrival mismatch and vehicle energy consumption under state-of-charge (SOC) and charger-capacity constraints, explicitly quantifying vehicle–crane alignment at both handling interfaces. Secondly, an enhanced multi-objective algorithm (ST-NSGA-II) is developed, integrating a feasibility-preserving recursive decoding mechanism and a spatio-temporal variable neighborhood search (VNS) procedure. Finally, numerical experiments demonstrate that ST-NSGA-II significantly reduces mismatch and energy consumption compared to standard NSGA-II in large-scale scenarios. It also outperforms MOEA/D in Pareto-set quality, yielding a higher hypervolume (1.301 vs. 0.960) and a lower Spacing value (0.102 vs. 0.185). The results demonstrate that the proposed spatio-temporal optimization approach can effectively reduce handover mismatch compared to conventional scheduling modes, thereby achieving seamless task scheduling for vehicle–crane coordination. Full article
(This article belongs to the Special Issue Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering)
►▼ Show Figures

Figure 1

19 pages, 6028 KB  
Article
Multi-View Point Cloud Registration Method for Automated Disassembly of Container Twist Locks
by Chao Mi, Teng Wang, Xintai Man, Mengjie He, Zhiwei Zhang and Yang Shen
J. Mar. Sci. Eng. 2026, 14(7), 605; https://doi.org/10.3390/jmse14070605 - 25 Mar 2026
Viewed by 440
Abstract
With the continuous expansion of maritime trade scale, ports have put forward increasingly higher requirements for transshipment efficiency. Container twist lock disassembly is a key link in the loading and unloading process, and its automation level has a significant impact on the ship’s [...] Read more.
With the continuous expansion of maritime trade scale, ports have put forward increasingly higher requirements for transshipment efficiency. Container twist lock disassembly is a key link in the loading and unloading process, and its automation level has a significant impact on the ship’s berthing time at the port. Aiming at the demand of automated disassembly for high-precision 3D vision, this paper proposes a multi-view point cloud local registration method for twist lock recognition. First, Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) is used to extract the keyhole region with the highest overlap in multi-view point clouds, reducing the interference from non-overlapping structures. Then, a two-stage strategy of “coarse registration + fine registration” is adopted: initial alignment is achieved through Random Sample Consensus (RANSAC), and the Iterative Closest Point (ICP) algorithm is improved by combining adaptive distance threshold and normal consistency constraint to complete fine registration. Experimental results show that the proposed method outperforms the global registration scheme in both accuracy and efficiency: the Root Mean Square Error (RMSE) is reduced to 2.15 mm, the Relative Mean Distance (RMD) is reduced to 1.81 mm, and the registration time is approximately 2.41 s. Compared with global registration, the efficiency is improved by 44.2%, which can meet the real-time requirements of continuous operation at automated terminals for the perception link and the time constraints for subsequent manipulator control. The research results preliminarily verify the application potential of this method in the scenario of automated twist lock disassembly. Full article
(This article belongs to the Special Issue Sustainable Maritime Transport, Ports, Supply Chain Intelligence, and Marine Environmental Engineering)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop