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Seas of Change: Advancing Sustainable Maritime and Freight Transportation via...
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Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors

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: closed (1 March 2024) | Viewed by 8023

Special Issue Editors

Prof. Dr. Paul Tae-Woo Lee

E-Mail Website
Guest Editor
Ocean College, Zhejiang University, Zhoushan 316021, China
Interests: maritime transport and logistics; green shipping corridors; Belt and Road Initiative
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jihong Chen

E-Mail Website
Guest Editor
College of Management, Shenzhen University, Shenzhen, China
Interests: green port and shipping; maritime pollution governance; sustainable port and shipping development
Prof. Dr. Theo Notteboom

E-Mail Website
Guest Editor
1. Maritime Institute, Ghent University, 9000 Ghent, Belgium
2. Faculty of Business and Economics, University of Antwerp, 2000 Antwerp, Belgium
Interests: port and maritime economics and management; port geography; intermodal transport; green supply chain management; strategic management
Dr. Guanqiong Ye

E-Mail Website
Guest Editor
Ocean College, Zhejiang University, Zhoushan 316021, China
Interests: marine spatial planning; coastal ecosystem assessment; marine environmental management; blue carbon and climate change

Special Issue Information

Dear Colleagues,

Since the Clydebank Declaration in 2011, green shipping corridors (GSCs) have become a focal issue in the maritime industry and international organizations. No less than ten major stakeholders are involved in launching and implementing GSCs. This Special Issue aims to publish the most exciting research covering greening issues in maritime and freight transportation and coastal areas, which are related to green fuels, digitalization and decarbonization, and to freely disseminate the articles for research, teaching, policy-making and reference purposes.

High-quality papers with novel research methods directly related to the topics mentioned below are encouraged for publication.

Topics

  • Green shipping corridor (GSC) for containers, LNGs, iron ores and cruises;
  • Decarbonization and digitalization of the maritime industry;
  • Deployment of zero-emission ships on GSC routes;
  • Green fuel supply chains;
  • Green and smart port operation and management;
  • Greening coastal management;
  • Environmental assessment of offshore shipping industry;

Prof. Dr. Paul Tae-Woo Lee
Prof. Dr. Jihong Chen
Prof. Dr. Theo Notteboom
Dr. Guanqiong Ye
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 100 words) can be sent to the Editorial Office for announcement on this website.

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 monthly 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

  • green shipping corridors
  • decarbonization and digitalization
  • green fuel supply chains
  • greening coastal management

Published Papers (5 papers)

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Research

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28 pages, 3632 KiB  
Article
Discovering Trends in the Digitalization of Shipping: An Exploratory Study into Trends Using Natural Language Processing
by Geoffrey Aerts and Guy Mathys
J. Mar. Sci. Eng. 2024, 12(4), 618; https://doi.org/10.3390/jmse12040618 - 04 Apr 2024
Viewed by 585
Abstract
This study investigates digitalization in the shipping industry by analyzing over 500 industry presentations from an eight-year span to discern key trends and nascent signals. Employing optical character recognition, advanced natural language processing techniques, and similarity metrics, the research enhances topic interpretability. Through [...] Read more.
This study investigates digitalization in the shipping industry by analyzing over 500 industry presentations from an eight-year span to discern key trends and nascent signals. Employing optical character recognition, advanced natural language processing techniques, and similarity metrics, the research enhances topic interpretability. Through Theil–Sen regressions and diffusion metrics, it identifies trends and emerging signals, noting a rise in interest in smart ports and supply chain management, signaling a shift toward more intelligent technology integration. However, attention to supply chain management shows a decline. The research tracks a shift from broad technology themes to specific areas like cybersecurity and blockchain, reflecting a narrative pivot to tackle particular digital challenges and opportunities. The study detects weak signals, including terms like “subsea” and “drone”, suggesting forthcoming industry innovations and shifts, notably toward ESG considerations. An additional machine learning analysis corroborates findings on key topics like energy efficiency and crew welfare, also spotlighting virtual disaster recovery and ERP projects as emerging areas of interest. This work aids in comprehending the fluid digitalization landscape in shipping, highlighting the sector’s ongoing evolution, and underscoring the need for further inquiry into autonomous shipping and related domains. Full article
(This article belongs to the Special Issue Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors)
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24 pages, 5463 KiB  
Article
Data- and Model-Driven Crude Oil Supply Risk Assessment of China Considering Maritime Transportation Factors
by Gangqiao Wang, Qianrong Yin, Mingzhu Yu and Jihong Chen
J. Mar. Sci. Eng. 2024, 12(1), 52; https://doi.org/10.3390/jmse12010052 - 25 Dec 2023
Viewed by 846
Abstract
Effective supply-chain risk assessment is the basis for developing sustainable supply policies, and it has received growing attention in global oil supply system management. Dynamical modeling and data-driven modeling are two main risk assessment technologies that have been applied in crude oil supply [...] Read more.
Effective supply-chain risk assessment is the basis for developing sustainable supply policies, and it has received growing attention in global oil supply system management. Dynamical modeling and data-driven modeling are two main risk assessment technologies that have been applied in crude oil supply networks. Dynamical risk modeling and data-driven risk modeling offer distinct advantages in capturing the complexities and dynamics of the system. Considering their complementary strengths, a hybrid modeling framework combining system dynamics and data-driven neural networks is proposed for risk assessment of crude oil transportation network. Specifically, the system dynamics module is to capture and interpret the underlying dynamics and mechanisms of the transportation network, while the deep neural networks module is to discover the nonlinear patterns and dependencies of risk factors from various inputs. Based on joint training, the hybrid model can ultimately develop the capability of risk prediction with a small amount of data. In addition, it can consider the dynamic nature of crude oil transportation networks to interpret the predicted results of the risk level for decision-makers to make specific risk-mitigating policies. Extensive experiments based on China’s scenario have been conducted to demonstrate the effectiveness of the proposed hybrid model, and the results show that our model achieves higher accuracy in risk prediction compared to the current state of the art. The results also present an explanation for China’s policy change of building a resilient crude oil transportation system. Full article
(This article belongs to the Special Issue Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors)
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24 pages, 5010 KiB  
Article
Multiple Container Terminal Berth Allocation and Joint Operation Based on Dueling Double Deep Q-Network
by Bin Li, Caijie Yang and Zhongzhen Yang
J. Mar. Sci. Eng. 2023, 11(12), 2240; https://doi.org/10.3390/jmse11122240 - 27 Nov 2023
Viewed by 875
Abstract
In response to the evolving challenges of the integration and combination of multiple container terminal operations under berth water depth constraints, the multi-terminal dynamic and continuous berth allocation problem emerges as a critical issue. Based on computational logistics, the MDC-BAP is formulated to [...] Read more.
In response to the evolving challenges of the integration and combination of multiple container terminal operations under berth water depth constraints, the multi-terminal dynamic and continuous berth allocation problem emerges as a critical issue. Based on computational logistics, the MDC-BAP is formulated to be a unique variant of the classical resource-constrained project scheduling problem, and modeled as a mixed-integer programming model. The modeling objective is to minimize the total dwelling time of linerships in ports. To address this, a Dueling Double DQN-based reinforcement learning algorithm is designed for the multi-terminal dynamic and continuous berth allocation problem A series of computational experiments are executed to validate the algorithm’s effectiveness and its aptitude for multiple terminal joint operation. Specifically, the Dueling Double DQN algorithm boosts the average solution quality by nearly 3.7%, compared to the classical algorithm such as Proximal Policy Optimization, Deep Q Net and Dueling Deep Q Net also have better results in terms of solution quality when benchmarked against the commercial solver CPLEX. Moreover, the performance advantage escalates as the number of ships increases. In addition, the approach enhances the service level at the terminals and slashes operation costs. On the whole, the Dueling Double DQN algorithm shows marked superiority in tackling complicated and large-scale scheduling problems, and provides an efficient, practical solution to MDC-BAP for port operators. Full article
(This article belongs to the Special Issue Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors)
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12 pages, 972 KiB  
Article
Solving the Inter-Terminal Truck Routing Problem for Delay Minimization Using Simulated Annealing with Normalized Exploration Rate
by Muhammad Hanif Ramadhan, Imam Mustafa Kamal, Dohee Kim and Hyerim Bae
J. Mar. Sci. Eng. 2023, 11(11), 2103; https://doi.org/10.3390/jmse11112103 - 02 Nov 2023
Viewed by 866
Abstract
The growth in containerized shipping has led to the expansion of seaports, resulting in the emergence of multiple terminals. While multi-terminal systems increase port capacity, they also pose significant challenges to container transportation, particularly in inter-terminal movements. Consequently, the transportation delay of containers [...] Read more.
The growth in containerized shipping has led to the expansion of seaports, resulting in the emergence of multiple terminals. While multi-terminal systems increase port capacity, they also pose significant challenges to container transportation, particularly in inter-terminal movements. Consequently, the transportation delay of containers in inter-terminal operations demands crucial attention, as it can adversely affect the efficiency and service levels of seaports. To minimize the total transportation delays of the inter-terminal truck routing problem (ITTRP), we introduce simulated annealing with normalized acceptance rate (SANE). SANE improves the exploration capability of simulated annealing (SA) by dynamic rescaling of the transportation delay objective to modify the acceptance probability. To validate the quality of solutions provided by SANE, we have developed a mathematical model that provides a set of linear formulations for ITTRP constraints, avoiding the known set-partitioning alternative. Experimental results showed that for small-scale ITTRP instances, SANE achieved a solution close to the optimal. In larger instances with 100–120 orders, SANE found feasible suboptimal solutions within 15–21 seconds, which is unattainable using the exact solver. Further comparison with baselines indicates that SANE provides considerable improvements compared to both SA and Tabu search in terms of the objective value. Full article
(This article belongs to the Special Issue Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors)
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Review

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28 pages, 4476 KiB  
Review
Applications, Evolutions, and Challenges of Drones in Maritime Transport
by Jingbo Wang, Kaiwen Zhou, Wenbin Xing, Huanhuan Li and Zaili Yang
J. Mar. Sci. Eng. 2023, 11(11), 2056; https://doi.org/10.3390/jmse11112056 - 27 Oct 2023
Cited by 3 | Viewed by 4008
Abstract
The widespread interest in using drones in maritime transport has rapidly grown alongside the development of unmanned ships and drones. To stimulate growth and address the associated technical challenges, this paper systematically reviews the relevant research progress, classification, applications, technical challenges, and possible [...] Read more.
The widespread interest in using drones in maritime transport has rapidly grown alongside the development of unmanned ships and drones. To stimulate growth and address the associated technical challenges, this paper systematically reviews the relevant research progress, classification, applications, technical challenges, and possible solutions related to the use of drones in the maritime sector. The findings provide an overview of the state of the art of the applications of drones in the maritime industry over the past 20 years and identify the existing problems and bottlenecks in this field. A new classification scheme is established based on their flight characteristics to aid in distinguishing drones’ applications in maritime transport. Further, this paper discusses the specific use cases and technical aspects of drones in maritime rescue, safety, navigation, environment, communication, and other aspects, providing in-depth guidance on the future development of different mainstream applications. Lastly, the challenges facing drones in these applications are identified, and the corresponding solutions are proposed to address them. This research offers pivotal insights and pertinent knowledge beneficial to various entities such as maritime regulatory bodies, shipping firms, academic institutions, and enterprises engaged in drone production. This paper makes new contributions in terms of the comprehensive analysis and discussion of the application of drones in maritime transport and the provision of guidance and support for promoting their further development and integration with intelligent transport. Full article
(This article belongs to the Special Issue Seas of Change: Advancing Sustainable Maritime and Freight Transportation via Decarbonization and Digitalization in Green Shipping Corridors)
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