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New Trends in Engineering and Operational Research on Container Supply...
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New Trends in Engineering and Operational Research on Container Supply Chain Management for Resilience, Digitalization, Intelligence and Sustainability

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: 20 October 2025 | Viewed by 2014

Special Issue Editors

Prof. Dr. Hongtao Hu

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Guest Editor
The Container Supply Chain Technology Engineering Research Center of the Ministry of Education, Logistics Engineering College, Shanghai Maritime University, Shanghai 201308, China
Interests: port operations; shipping; logistics; supply chain
Prof. Dr. Tingsong Wang

E-Mail Website
Guest Editor
School of Management, Shanghai University, Shanghai 200444, China
Interests: maritime transportation; network modeling; operations research
Special Issues, Collections and Topics in MDPI journals
Dr. Yiwei Wu

E-Mail Website
Guest Editor
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hung Hom, Hong Kong
Interests: large-scale optimization; decision making under uncertainty; data-driven decision making; green shipping management; smart transportation
Special Issues, Collections and Topics in MDPI journals
Dr. Shuai Jia

E-Mail Website
Guest Editor
Thrust of Intelligent Transportation, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Interests: data-driven modeling and optimization; decision support systems; transportation and logistics management

Special Issue Information

Dear Colleagues,

Container transportation serves as the cornerstone of global economic integration and the smooth, efficient operation of global supply chains. In recent years, with escalating geopolitical conflicts, the rise in anti-globalization trends, technological transformations, stricter emissions regulations, and innovations in port operations have brought both challenges and opportunities for container supply chain management, particularly in maritime shipping. Therefore, it is critical to enhance the resilience, digitization, intelligence, and sustainability of container shipping management.

This Special Issue focuses on presenting new engineering or operational research related to container port operations, container logistics for port entry and exit, hinterland connectivity, and container shipping management. Key areas of interest include performance monitoring and enhancement in resilience, digitization, intelligence, and sustainability across various aspects of container transport, such as port operations, shipping management, multimodal transport, and inland waterways. Some specific areas are (i) the optimization of maritime networks, container port operations, and route planning, as well as logistics for trucks, rail, or barges accessing terminals; (ii) the application of emerging technologies—such as digitization, big data, artificial intelligence (AI), digital twins, blockchain, autonomous vessels, and drones—in port and shipping management; (iii) the use of LNG-powered ships, electric vessels, alternative maritime fuels, and strategies for low-carbon, green, and sustainable container shipping; and (iv) managing disruptions and emergencies, along with risk analysis and control in maritime operations. The modeling employed might include artificial intelligence, machine learning, routing and cargo load planning, facilities layout and design, or automation design.

We welcome the submission of both general and case-based articles that are analytically oriented with a focus on engineering from academic and professional researchers and practitioners to explore this area further.

Prof. Dr. Hongtao Hu
Prof. Dr. Tingsong Wang
Dr. Yiwei Wu
Dr. Shuai Jia
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

  • container logistics
  • maritime shipping
  • sustainable supply chain
  • emerging technologies
  • disruptions and emergencies
  • operations and management
  • mathematical programming
  • combinatorial optimization

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Published Papers (4 papers)

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Research

25 pages, 3182 KiB  
Article
From Efficiency to Safety: A Simulation-Based Framework for Evaluating Empty-Container Terminal Layouts
by Cristóbal Vera-Carrasco, Cristian D. Palma and Sebastián Muñoz-Herrera
J. Mar. Sci. Eng. 2025, 13(8), 1424; https://doi.org/10.3390/jmse13081424 - 26 Jul 2025
Viewed by 108
Abstract
Empty container depot (ECD) design significantly impacts maritime terminal efficiency, yet traditional evaluation approaches assess limited operational factors, constraining comprehensive performance optimization. This study develops an integrated discrete event simulation (DES) framework that simultaneously evaluates lifting equipment utilization, truck turnaround times, and potential [...] Read more.
Empty container depot (ECD) design significantly impacts maritime terminal efficiency, yet traditional evaluation approaches assess limited operational factors, constraining comprehensive performance optimization. This study develops an integrated discrete event simulation (DES) framework that simultaneously evaluates lifting equipment utilization, truck turnaround times, and potential collisions to support terminal decision-making. This study combines operational efficiency metrics with safety analytics for non-automated ECDs using Top Lifters and Reach Stackers. Additionally, a regression analysis examines efficiency metrics’ effect on safety risk. A case study at a Chilean multipurpose terminal reveals performance trade-offs between indicators under different operational scenarios, identifying substantial efficiency disparities between dry and refrigerated container operations. An analysis of four distinct collision zones with varying historical risk profiles showed the gate area had the highest potential collisions and a strong regression correlation with efficiency metrics. Similar models showed a poor fit in other conflict zones, evidencing the necessity for dedicated safety indicators complementing traditional measures. This integrated approach quantifies interdependencies between safety and efficiency metrics, helping terminal managers optimize layouts, expose traditional metric limitations, and reduce safety risks in space-constrained maritime terminals. Full article
(This article belongs to the Special Issue New Trends in Engineering and Operational Research on Container Supply Chain Management for Resilience, Digitalization, Intelligence and Sustainability)
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30 pages, 3858 KiB  
Article
An Assessment of Shipping Network Resilience Under the Epidemic Transmission Using a SEIR Model
by Bo Song, Lei Shi and Zhanxin Ma
J. Mar. Sci. Eng. 2025, 13(6), 1166; https://doi.org/10.3390/jmse13061166 - 13 Jun 2025
Viewed by 461
Abstract
Epidemics spread through shipping networks and have dual characteristics as both biological sources of infection and triggers of cascading failures. However, existing resilience models fail to capture this dual and coupled dynamics. To minimize the cascading impacts of epidemics on global shipping networks, [...] Read more.
Epidemics spread through shipping networks and have dual characteristics as both biological sources of infection and triggers of cascading failures. However, existing resilience models fail to capture this dual and coupled dynamics. To minimize the cascading impacts of epidemics on global shipping networks, this paper proposes an innovative resilience assessment framework that considers the interaction between epidemic transmission and the shipping network cascading failure. First, a weighted shipping network topology is constructed based on route flow characteristics to quantify route frequency, stopping time, and the number of infected people, and the epidemic transmission across ports is modeled with an improved SEIR model, which contains a heterogeneous infectivity function and a dynamic transmission matrix, revealing a dual transmission mechanism inside and outside the ports. Second, a two-stage cascading failure model is developed: a direct failure triggered by infected people exceeding the threshold and an indirect failure triggered by the dynamic redistribution of loads. The load redistribution strategy is optimized to reconcile the residual port capacity and the risk of infection. Finally, a multidimensional resilience assessment framework covering structural destruction resistance, network efficiency, path redundancy, and a cascading failure propagation rate is constructed. Example validation shows that the improved load redistribution strategy reduces the maximum connected subgraph decay rate by 68.2%, reduces the cascading failure rate by 88%, and improves the peak network efficiency by 128.2%. In case of multi-source epidemics, the state of the network collapse can be shortened by 12 days if the following recovery strategy is adopted: initially repair high connectivity hubs (e.g., Port of Shanghai), and then repair high centrality nodes (e.g., Antwerp Port) to achieve a balance between recovery efficiency and network functionality. The research results reduce the risk of systemic disruptions in maritime networks and provide decision-making tools for dynamic port scheduling during pandemics. Full article
(This article belongs to the Special Issue New Trends in Engineering and Operational Research on Container Supply Chain Management for Resilience, Digitalization, Intelligence and Sustainability)
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21 pages, 1748 KiB  
Article
Energy-Efficient Scheduling for Resilient Container-Supply Hybrid Flow Shops Under Transportation Constraints and Stochastic Arrivals
by Huaixia Shi, Huaqiang Si and Jiyun Qin
J. Mar. Sci. Eng. 2025, 13(6), 1153; https://doi.org/10.3390/jmse13061153 - 11 Jun 2025
Viewed by 280
Abstract
Although dynamic, energy-efficient container-supply hybrid flow shops have attracted increasing attention, most existing research overlooks how transportation within container production affects makespan, resilience, and sustainability. To bridge this gap, we frame a resilient, energy-efficient container-supply hybrid flow shop (TDEHFSP) scheduling model that utilizes [...] Read more.
Although dynamic, energy-efficient container-supply hybrid flow shops have attracted increasing attention, most existing research overlooks how transportation within container production affects makespan, resilience, and sustainability. To bridge this gap, we frame a resilient, energy-efficient container-supply hybrid flow shop (TDEHFSP) scheduling model that utilizes vehicle transportation to maximize operational efficiency. To address the TDEHFSP model, the study proposes a Q-learning-based multi-swarm collaborative optimization algorithm (Q-MGCOA). The algorithm integrates a time gap left-shift scheduling strategy with a machine on–off control mechanism to construct an energy-saving optimization framework. Additionally, a predictive–reactive dynamic rescheduling model is introduced to address unexpected task disturbances. To validate the algorithm’s effectiveness, 36 benchmark test cases with varying scales are designed for horizontal comparison. Results show that the proposed Q-MGCOA outperforms benchmarks on convergence, diversity, and supply-chain resilience while lowering energy utilization. Moreover, it achieves about an 8% reduction in energy consumption compared to traditional algorithms. These findings reveal actionable insights for next-generation intelligent, low-carbon container production. Full article
(This article belongs to the Special Issue New Trends in Engineering and Operational Research on Container Supply Chain Management for Resilience, Digitalization, Intelligence and Sustainability)
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26 pages, 2728 KiB  
Article
Deploying Liquefied Natural Gas-Powered Ships in Response to the Maritime Emission Trading System: From the Perspective of Shipping Alliances
by Yulong Sun, Jianfeng Zheng, Xin He, Zhihao Zhao and Di Cui
J. Mar. Sci. Eng. 2025, 13(3), 551; https://doi.org/10.3390/jmse13030551 - 12 Mar 2025
Cited by 1 | Viewed by 638
Abstract
In response to climate change caused by shipping, the maritime emission trading system (METS) is used to reduce ship carbon emissions, and the METS also imposes additional costs on shipping carriers through emission permit trading. This paper focuses on the deployment of liquefied [...] Read more.
In response to climate change caused by shipping, the maritime emission trading system (METS) is used to reduce ship carbon emissions, and the METS also imposes additional costs on shipping carriers through emission permit trading. This paper focuses on the deployment of liquefied natural gas-powered (LNG-powered) ships for shipping alliances to comply with the METS. From the perspective of a liner alliance, we investigate how to determine the deployment of LNG-powered ships and how ship emissions will be affected. To investigate these problems, we propose an LNG-powered fleet deployment problem, which integrates slot co-chartering and emission permit trading, to determine the fleet deployment of LNG-powered and oil-powered ships, ship speeds and container shipment. To formulate our proposed problem, we develop a mixed-integer linear programming model, which can be solved effectively by CPLEX. Numerical experiments are provided to assess the effectiveness of our proposed model. Full article
(This article belongs to the Special Issue New Trends in Engineering and Operational Research on Container Supply Chain Management for Resilience, Digitalization, Intelligence and Sustainability)
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