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Recent Advances in Intelligent Port Logistics
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Recent Advances in Intelligent Port Logistics

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

Deadline for manuscript submissions: closed (1 January 2024) | Viewed by 8456

Special Issue Editors

Prof. Dr. Yu Zhang

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Guest Editor
School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
Interests: operation management of port; port and shipping logistics; simulation of complex system
Prof. Dr. Jie Ma

E-Mail Website
Guest Editor
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Interests: information fusion perception; ship intelligent navigation and spatiotemporal services
Dr. Wenyuan Wang

E-Mail Website
Guest Editor
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Interests: green port spatial planning; intelligent scheduling of port production system
Special Issues, Collections and Topics in MDPI journals
Dr. Xiuwen Fu

E-Mail Website
Guest Editor
Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: Internet of Things; wireless sensor networks; unmanned systems; swarm intelligence; network reliability; network modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Background: Port logistics plays an important role in international trade, bearing over 70% of the import and export cargo volume. With the deep integration of artificial intelligence, big data, Internet of Things, and port logistics, port logistics has gradually become intelligent, digital, and green, which is of great significance for improving the efficiency of port logistics. At present, intelligent port logistics involves several intelligent applications, such as port planning and production scheduling, the collaborative scheduling of multiple machines, traffic organization, collection and distribution, integrated management and control, etc. These intelligent applications cannot be separated from operations research optimization, artificial intelligence, Internet of Things, digital twin, and other technologies. In order to promote the innovative development of intelligent port logistics and improve the efficiency of intelligent port logistics, it is necessary to focus on the innovation of port intelligent scheduling, unmanned truck transportation organization, port supply chain, port blockchain, port digital twin integrated control, and other aspects.  

To address these challenges, this Special Issue of the Journal of Marine Science and Engineering aims to showcase the recent developments in intelligent port logistics. We welcome papers that present new research contributions in this area, with a focus on real-world examples that demonstrate scientific advances and their practical implications. Topics of interest include, but are not limited to:

  • Intelligent port logistics production organization optimization;
  • Intelligent port logistics collection and distribution;
  • Port intelligent control based on digital twin;
  • Low-carbon and zero-carbon logistics of intelligent port;
  • Global supply chain of intelligent port logistics;
  • Multi-mode organization of intelligent port logistics;
  • Collaborative scheduling of multiple machines in intelligent port;
  • Intelligent port logistics simulation optimization.

Prof. Dr. Yu Zhang
Prof. Dr. Jie Ma
Dr. Wenyuan Wang
Dr. Xiuwen Fu
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

  • intelligent port
  • port logistics
  • production scheduling
  • optimization
  • machine learning
  • digital twin
  • Internet of Things

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

Published Papers (5 papers)

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Research

26 pages, 6019 KiB  
Article
Energy-Aware Integrated Scheduling for Quay Crane and IGV in Automated Container Terminal
by Yuedi Luo, Xiaolei Liang, Yu Zhang, Kexin Tang and Wenting Li
J. Mar. Sci. Eng. 2024, 12(3), 376; https://doi.org/10.3390/jmse12030376 - 22 Feb 2024
Cited by 1 | Viewed by 1294
Abstract
In this study, we address the integrated scheduling problem involving quay cranes and IGVs in automated terminals. We construct a mixed-integer planning model with the aim of minimizing the total energy consumption during quay crane and IGV operations, focusing on the loading-operation mode. [...] Read more.
In this study, we address the integrated scheduling problem involving quay cranes and IGVs in automated terminals. We construct a mixed-integer planning model with the aim of minimizing the total energy consumption during quay crane and IGV operations, focusing on the loading-operation mode. The model considers the impact of the actual stowage of container ships on the loading order. We propose a dimension-by-dimension mutation sparrow search algorithm to optimize the model’s solution quality. Building upon the standard sparrow search algorithm, we incorporate cat mapping to enhance the diversity of the initial sparrow population. To improve global search in the early stage and local search in the later stage of the algorithm, we introduce an adaptive t-distribution mutation strategy. Finally, a total of 12 instances with container counts containing 30, 100, and 250 were designed for experiments to validate the effectiveness of the model and algorithm. The experiments demonstrate that, by appropriately increasing the number of quay cranes, configuring more than two or three IGVs can achieve optimal energy consumption for overall operations. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Port Logistics)
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19 pages, 1463 KiB  
Article
Automatic Guided Vehicle Scheduling in Automated Container Terminals Based on a Hybrid Mode of Battery Swapping and Charging
by Shichang Xiao, Jinshan Huang, Hongtao Hu and Yuxin Gu
J. Mar. Sci. Eng. 2024, 12(2), 305; https://doi.org/10.3390/jmse12020305 - 9 Feb 2024
Cited by 1 | Viewed by 1422
Abstract
Automatic guided vehicles (AGVs) in the horizontal area play a crucial role in determining the operational efficiency of automated container terminals (ACTs). To improve the operational efficiency of an ACT, it is essential to decrease the impact of battery capacity limitations on AGV [...] Read more.
Automatic guided vehicles (AGVs) in the horizontal area play a crucial role in determining the operational efficiency of automated container terminals (ACTs). To improve the operational efficiency of an ACT, it is essential to decrease the impact of battery capacity limitations on AGV scheduling. To address this problem, this paper introduces battery swapping and opportunity charging modes into the AGV system and proposes a new AGV scheduling problem considering the hybrid mode. Firstly, this study describes the AGV scheduling problem of the automated container terminals considering both loading and unloading tasks under the hybrid mode of battery swapping and charging. Thereafter, a mixed-integer programming model is established to minimize the sum of energy costs and delay costs. Secondly, an effective adaptive large neighborhood search algorithm is proposed to solve the problem, in which the initial solution construction, destroy operators, and repair operators are designed according to the hybrid mode. Finally, numerical experiments are conducted to analyze the effectiveness of the model and the optimization performance of the algorithm. The results demonstrate that the hybrid mode of battery swapping and charging can effectively reduce the number of battery swapping times and scheduling costs compared to the existing mode. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Port Logistics)
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36 pages, 1778 KiB  
Article
Integrated Inbound and Outbound Scheduling for Coal Port: Constraint Programming and Adaptive Local Search
by Xuan Lu, Yu Zhang, Lanbo Zheng, Caiyun Yang and Junjie Wang
J. Mar. Sci. Eng. 2024, 12(1), 124; https://doi.org/10.3390/jmse12010124 - 8 Jan 2024
Cited by 1 | Viewed by 1550
Abstract
The effective production scheduling of dry bulk ports is a challenging task that demands meticulous planning, task allocation based on customer requirements, as well as strategic route and timing scheduling. Dry bulk ports dedicated to handling commodities like coal and iron ore frequently [...] Read more.
The effective production scheduling of dry bulk ports is a challenging task that demands meticulous planning, task allocation based on customer requirements, as well as strategic route and timing scheduling. Dry bulk ports dedicated to handling commodities like coal and iron ore frequently engage in blending operations as a strategic imperative to gain market competitiveness. The process of blending coal and ore entails the timely arrival of the requisite raw materials at predetermined locations. Simultaneously, it necessitates the coordination of the sequencing of goods entering and departing the port to align with the operational demands associated with material stockpiles. This paper describes and analyzes an operational scheduling problem encountered by one of the largest coal blending sea ports in China. Specifically, a rich constraint programming model is presented to define operation sequences integrating daily inbound and outbound services provided by the port, minimizing the overall operation time. In order to enhance the practicality of the method, a CP-based adaptive simulated annealing local search algorithm has been designed and developed for the optimization problem. The empirical validation of the proposed method is conducted using both real production data and generated experimental data adhering to specific rules. The results conclusively demonstrate the efficacy and feasibility of the proposed method. This also substantiates its practicality and effectiveness in real-world applications, facilitating efficient production and energy-saving operations for the coal port. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Port Logistics)
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26 pages, 6910 KiB  
Article
Research on the Multi-Equipment Cooperative Scheduling Method of Sea-Rail Automated Container Terminals under the Loading and Unloading Mode
by Yongsheng Yang, Shu Sun, Sha He, Yajia Jiang, Xiaoming Wang, Hong Yin and Jin Zhu
J. Mar. Sci. Eng. 2023, 11(10), 1975; https://doi.org/10.3390/jmse11101975 - 12 Oct 2023
Cited by 6 | Viewed by 1629
Abstract
A sea-rail automated container terminal (SRACT) plays a crucial role in the global logistics network, combining the benefits of sea and railway transportation. However, addressing the challenges of multi-equipment cooperative scheduling in terminal and railway operation areas is essential to ensure efficient container [...] Read more.
A sea-rail automated container terminal (SRACT) plays a crucial role in the global logistics network, combining the benefits of sea and railway transportation. However, addressing the challenges of multi-equipment cooperative scheduling in terminal and railway operation areas is essential to ensure efficient container transportation. For the first time, this study addresses the cooperative scheduling challenges among railway gantry cranes, yard cranes, and automated guided vehicles (AGVs) under the loading and unloading mode in SRACTs, ensuring efficient container transportation. This requires the development of a practical scheduling model and algorithm. In this study, a mixed integer programming model was established for the first time to study the multi-equipment cooperative scheduling problem of a SRACT under the loading and unloading mode. A self-adaptive chaotic genetic algorithm was designed to solve the model, and the practicability and effectiveness of the model and algorithm were verified by simulation experiments. Furthermore, this study also proposes an AGV number adjustment strategy to accommodate changes in vessel arrival delays and train container types. Simulation experiments demonstrated that this strategy significantly reduces loading and unloading time, decreases equipment energy consumption, and improves the utilization rate of AGVs. This research provides valuable guidance for ongoing SRACT projects and advances and methodological approaches in multi-equipment co-operative scheduling for such terminals. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Port Logistics)
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19 pages, 1707 KiB  
Article
Enhanced Multi-Objective Evolutionary Algorithm for Green Scheduling of Heterogeneous Quay Cranes Considering Cooperative Movement and Safety
by Lingchong Zhong, Lijun He, Yongcui Li, Yu Zhang, Yong Zhou and Wenfeng Li
J. Mar. Sci. Eng. 2023, 11(10), 1884; https://doi.org/10.3390/jmse11101884 - 28 Sep 2023
Cited by 2 | Viewed by 1167
Abstract
Heterogeneous quay cranes (HQCs) are the main energy-consuming equipment of automated container terminals, and they need to move from one bay to another along the rail and maintain a safe distance from one another. Improving the operational efficiency of HQCs and reducing the [...] Read more.
Heterogeneous quay cranes (HQCs) are the main energy-consuming equipment of automated container terminals, and they need to move from one bay to another along the rail and maintain a safe distance from one another. Improving the operational efficiency of HQCs and reducing the ineffective walking distance of HQCs are key to reducing the energy consumption of QCs. In this paper, an energy-efficient HQC cooperative scheduling problem is studied, and the HQCs are required to ensure safe and efficient operation. A multi-objective scheduling model is formulated to minimize the maximum completion time of containers, the average completion time of HQCs, and the total energy consumption of HQCs simultaneously. An Enhanced Multi-Objective Evolutionary Algorithm (EMOEA) is designed to solve this problem using a problem-feature-based encoding method to encode and initialize the population, a cooperative strategy to ensure the safe operating distance of HQCs, and a novel multi-objective evaluation mechanism with effective evolutionary operators. The results indicate that the different operational capacities of HQCs had a significant impact on the three studied objectives, especially for some large-scale problems, and that our algorithm outperforms three other well-known multi-objective algorithms in solving the EHQCCSP. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Port Logistics)
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