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Advances in Marine Logistics, Shipping, and Ports
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Advances in Marine Logistics, Shipping, and Ports

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).

Deadline for manuscript submissions: closed (5 October 2023) | Viewed by 7533

Special Issue Editor

Prof. Dr. Nam Kyu Park

E-Mail Website
Guest Editor
1. Former Professor, International Port and Logistics Department, Tongmyung University, Busan 48520, Republic of Korea
2. Logi AI Innovation Lab, T2L, Koyang 1545, Republic of Korea
Interests: port automation; port capacity; container terminal automation; port productivity; port environment, energy, port information system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to the multidisciplinary field that focuses on improving the efficiency and sustainability of maritime logistics systems.

This area of study is closely linked to the growth of international trade and globalization. Over the years, the field has evolved to address various challenges such as the increasing size of vessels, changing environmental regulations, and the need for greater efficiency in the field.

This field aims to enhance the effectiveness and efficiency of marine logistics by developing innovative technologies and methodologies. The scope of this field includes a range of topics, such as simulation, AI, automation, big data analysis, IOT and information platform in the areas of shipping, ports, and logistics. 

We invite researchers in these areas to submit papers that address the challenges and opportunities of marine logistics, shipping, and ports, and provide innovative solutions in order to improve the efficiency and sustainability of maritime transportation. We are particularly interested in papers that combine theoretical analysis with practical applications and offer insights into the latest trends and developments in the field.

Prof. Dr. Nam Kyu Park
Guest Editor

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

  • logistics platform
  • AI
  • port automation
  • green shipping
  • big data
  • autonomous vehicle

Published Papers (4 papers)

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Research

22 pages, 4369 KiB  
Article
Yard Space Allocation Algorithm for Unloading Containers at Marine Terminals
by Xingyu Wang, Ning Zhao and Chao Mi
J. Mar. Sci. Eng. 2023, 11(11), 2109; https://doi.org/10.3390/jmse11112109 - 04 Nov 2023
Viewed by 1068
Abstract
The issue of unloading efficiency for containers is the operational bottleneck for most traditional container terminals. In addressing the intricate challenges of space allocation in container yards during ship unloading, this study focuses on the real-time, dynamic decision-making needs that are currently unmet [...] Read more.
The issue of unloading efficiency for containers is the operational bottleneck for most traditional container terminals. In addressing the intricate challenges of space allocation in container yards during ship unloading, this study focuses on the real-time, dynamic decision-making needs that are currently unmet by existing planning methods. To tackle this, the article introduces a novel model for container space allocation that aims to maximize the “attractiveness” of yard spaces. This model factors in key considerations like the allocation of container handling equipment resources, the rate of container handling equipment traversing the yard, and container handling equipment operations across containers. A unique Monte Carlo tree search (MCTS)-based algorithm is developed to solve this multi-objective problem. The algorithm’s efficacy is rigorously tested via numerical experiments, where it outperforms existing approaches like UCT-MCTS, AMAF-MCTS, and manual scheduling plans using practical engineering examples. This research not only provides a more dynamic and efficient method for yard space allocation but also offers empirical evidence to support its practicality and effectiveness. Full article
(This article belongs to the Special Issue Advances in Marine Logistics, Shipping, and Ports)
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24 pages, 1418 KiB  
Article
Optimization of Fleet Scrubber Installation and Utilization Considering Sulfur Emission Control Areas and Marine Fuel Switching
by Jingwen Qi, Ruijun Feng and Shuaian Wang
J. Mar. Sci. Eng. 2023, 11(10), 1849; https://doi.org/10.3390/jmse11101849 - 22 Sep 2023
Viewed by 1243
Abstract
With the rising environmental consciousness, emission pollution has become one of the major concerns of the maritime industry, which is the artery of international trade. To handle the significant cost increase resulting from stringent emission regulations, ship operators have adopted multiple methods, including [...] Read more.
With the rising environmental consciousness, emission pollution has become one of the major concerns of the maritime industry, which is the artery of international trade. To handle the significant cost increase resulting from stringent emission regulations, ship operators have adopted multiple methods, including operational and technical methods. Scrubbers are a mature and effective technology that can reduce sulfur dioxide and particulate matter emissions by cleaning the exhaust gases before emitting them. However, the existing literature regarding the operation of scrubbers does not consider the prohibition of open scrubber usage in the vicinity of certain ports or the variable costs of using scrubbers. Therefore, this study explores the fleet scrubber installation and utilization problem, considering sulfur emission control areas, marine fuel switching, and open-scrubber-prohibited areas. A mixed-integer nonlinear model was developed to formulate and address the problem. Numerical experiments and sensitive analyses based on practical data were conducted to validate the originally proposed model and show the effectiveness of this technology under various scenarios. The results indicated that the operational cost was effectively reduced by using scrubbers, compared to not using them. Additionally, the disparity between total costs with and without scrubbers was significant, regardless of the sailing speed and proportion of the regulation areas. It was also proven that spreading the scrubber installation work over several years will relieve financial pressures due to scrubber investment and thus obtain a better installation plan. Full article
(This article belongs to the Special Issue Advances in Marine Logistics, Shipping, and Ports)
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29 pages, 12226 KiB  
Article
A Comparative Study of Machine Learning Models for Predicting Vessel Dwell Time Estimation at a Terminal in the Busan New Port
by Jeong-Hyun Yoon, Se-Won Kim, Ji-Sung Jo and Ju-Mi Park
J. Mar. Sci. Eng. 2023, 11(10), 1846; https://doi.org/10.3390/jmse11101846 - 22 Sep 2023
Cited by 1 | Viewed by 1637
Abstract
Container shipping plays a pivotal role in global trade, and understanding the duration that vessels spend in ports is crucial for efficient voyage planning by shipping companies. However, these companies often rely solely on one-way communication for required arrival times provided by terminals. [...] Read more.
Container shipping plays a pivotal role in global trade, and understanding the duration that vessels spend in ports is crucial for efficient voyage planning by shipping companies. However, these companies often rely solely on one-way communication for required arrival times provided by terminals. This reliance on fixed schedules can lead to vessels arriving punctually, only to face berths that are still occupied, resulting in unnecessary waiting times. Regrettably, limited attention has been given to these issues from the perspective of shipping companies. This study addresses this gap by focusing on the estimation of dwell times for container vessels at a terminal in the Port of Busan using various machine learning techniques. The estimations were compared against the terminal’s operational reference. To compile the dataset, a 41-month history of terminal berth schedules and vessel particulars data were utilized and preprocessed for effective training. Outliers were removed, and dimensions were reduced. Six regression machine learning algorithms, namely adaptive learning, gradient boosting, light gradient boosting, extreme gradient boosting, categorical boosting and random forest, were employed, and their parameters were fine-tuned for optimal performance on the validation dataset. The results indicated that all models exhibited superior performance compared to the terminal’s operating reference model. Full article
(This article belongs to the Special Issue Advances in Marine Logistics, Shipping, and Ports)
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20 pages, 40051 KiB  
Article
Chances and Challenges: Transformation from a Laser-Based to a Camera-Based Container Crane Automation System
by Johannes Benkert, Robert Maack and Tobias Meisen
J. Mar. Sci. Eng. 2023, 11(9), 1718; https://doi.org/10.3390/jmse11091718 - 31 Aug 2023
Cited by 1 | Viewed by 1274
Abstract
In recent years, a steady increase in maritime business and annual container throughput has been recorded. To meet this growing demand, terminal operators worldwide are turning to automated container handling. For the automated operation of a crane, a reliable capture of the environment [...] Read more.
In recent years, a steady increase in maritime business and annual container throughput has been recorded. To meet this growing demand, terminal operators worldwide are turning to automated container handling. For the automated operation of a crane, a reliable capture of the environment is required. In current state-of-the-art applications this is mostly achieved with light detection and ranging (LiDAR) sensors. These sensors enable precise three-dimensional sampling of the surroundings, even at great distances. However, the use of LiDAR sensors has a number of disadvantages, such as high acquisition costs and limited mounting positions. This raises the question of whether the LiDAR systems of automated container terminals (ACT) can be replaced with cameras. However, this transformation is not easy to accomplish and is explored in more depth in this paper. The field of camera-based container automation presented in this publication is largely unexplored. To the best of our knowledge, there is currently no automated container terminal in real-world operation that exclusively uses cameras. This publication aims to create a basis for further scientific research towards the goal of a fully camera-based container automation. Therefore, the authors present a narrative review providing a broad overview of the mentioned transformation, identifying research gaps, and suggesting areas for future research. In order to achieve this, this publication examines the fundamentals of an automated container terminal, the existing automation solutions and sensor technologies, as well as the opportunities and challenges of a transformation from LiDAR to camera. Full article
(This article belongs to the Special Issue Advances in Marine Logistics, Shipping, and Ports)
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