Container Terminals Research Articles

ANALYSIS OF COST AND TIME EFFICIENCY IN CONTAINER DISTRIBUTION BETWEEN CONTAINER TRUCK AND FREIGHT TRAIN FROM INDUSTRIAL AREA TO PORT

Jakarta International Container Terminal (JICT) in Tanjung Priok Port , which serves export and import containers, can serve up to 5500 TEUs daily. However, no more than 1% of the total containers are transported by freight trains, meaning that 99% of container distribution from industrial areas is carried by trailer trucks. This condition causes a long queue at the container terminal entrance, resulting in delays in the services as well. Currently, Tanjung Priok Port is connected to rail transportation from Cikarang dry port with the frequency of twice a day with 30 flatcars (FC) for each trip. The capacity of one series of freight trains from Cikarang dry port to Tanjung Priok Port can reach 30 Feus or 60 Teus. However, the container distribution using freight trains is still less optimal because of the double handling at the JICT emplacement which is located outside JICT and the use of trailer trucks to move the containers from the area to JICT. The cost of transporting export and import containers always increases year by year because of the slow transportation due to inefficiency of the container depot location in Tanjung Priok area. In this research, the method used to determine the efficiency of container transportation is divided into three scenarios. The first scenario is when the container is fully transported by truck from the industrial area. The second scenario is when the container is transported by train and handled twice while entering JICT. Finally, the third scenario is when the JICT emplacement is located inside the JICT area, changing the business process of containers coming in and out, needing no stacking in the JICT container yard, relocating the container depot placement, consolidating containers, and automating equipment at JICT to reduce the cost and time of containers for export and import. After analyzing the costs and time of the three scenarios, it was found that the third scenario could reduce travel costs and shorten container time when exporting and importing. The 3rd scenario can reduce the cost by almost 50% from the 1st and 2nd scenarios due to container consolidation.

A Comprehensive Study on Static and Dynamic Operational Efficiency in Major Korean Container Terminals Amid the Smart Port Development Context

A Comprehensive Study on Static and Dynamic Operational Efficiency in Major Korean Container Terminals Amid the Smart Port Development Context

Social network analysis of foreign research in the field of automation of cargo container transportation

The relevance of the topic is caused by the following. Improving automation and digitalization of technological processes of transshipment complexes is one of the priorities for development of maritime and river transport in the Russian Federation in the coming years. The importance of scientific research aimed at finding solutions to this problem, undoubtedly, increases already accumulated knowledge and the rate of emergence of new ones in this area. As a result, there is a need to update and systematize newly obtained theoretical and practical developments in review studies, which undoubtedly form the foundation of all academic research activities, as they are aimed at identifying current problems and links of future scientific developments with existing ones. The work analyzes the scientific area research in the field of automation of technological processes of container terminals regarding the dominant thematic areas of foreign scientific schools over the past ten years. The source of information flow for the analysis was secondary open scientific data posted in the GoogleScholar system. The objectives of the study included searching for publications corresponding to the stated topic, clustering the authors of these articles based on the principle of co-authorship, identifying scientists who contributed most to the new scientific developments, determining the scientific interests of researchers by analyzing the texts of their scientific works. The method of edge clustering, as well as structural and positional analyses were used to solve the tasks. As a result, a network graph was generated for the authorship of scientific works, a cross-citation graph of scientific publications, as well as a graph for comparing the research results of scientists with one of the thematic directions of the subject area of research. Graph construction and analysis were performed using Gephi software.

Pavement structures for extra heavy loads at multimodal traffic terminals

The subject matter of this study entails a brief overview of some of the methods for dimensioning pavement structures at container terminals, primarily located within ports and within freight rail stations, designed to withstand the loads imposed by very heavy vehicles (Heavy Duty Pavements). Within this study, an examination is provided on the methods for dimensioning cement concrete pavement structures for non-standard axle loads, as well as the results obtained through the application of these methods.

Bi-Objective Combinatorial Optimization Model for Emission Reduction Projects at Container Terminals Considering Investment Amount and Reduction Efficiency

Bi-Objective Combinatorial Optimization Model for Emission Reduction Projects at Container Terminals Considering Investment Amount and Reduction Efficiency

An Integrated Mathematical Framework for Optimizing Quay and Yard Design in Container Terminals

An Integrated Mathematical Framework for Optimizing Quay and Yard Design in Container Terminals

Improved Benders decomposition for stack-based yard template generation in an automated container terminal

Automated container terminals have become popular solutions to the growing need for container handling. We propose a two-stage mathematical model to design an efficient yard template for automated container terminals, using stacks as the allocation unit. In the first stage, a bi-objective model is developed to optimize landside and seaside operations in the terminal. A Benders decomposition algorithm is designed to solve the model. The proposed algorithm is improved by several acceleration strategies, including valid inequalities, pareto-optimal cuts, and ε−optimal approach. Drawing upon the solution derived from the first stage, the second stage assigns containers to specific bays, which is partitioned into multiple subproblems by capitalizing on the structure of it to enhance solvability. Numerous numerical experiments are conducted to verify the efficiency of the proposed algorithm. In addition, scenario analysis demonstrate that the stack-based yard template is more efficient than a cluster-based yard template for automated container terminals with multiple targets.

A multi-agent reinforcement learning approach for ART adaptive control in automated container terminals

Intelligent transportation equipment represented by Artificial Intelligence Robot of Transportation (ART) has been gradually applied to automated container terminals (ACT). ARTs have higher intelligence and distributed autonomous decision-making capability compared to AGVs. The production and operation of ACT require strict loading plans based on container types and destination ports, which puts strict requirements on the ART loading task sequence. ART travel time from the yard to the quay is highly uncertain due to special scenarios such as traffic flow convergence and turning in narrow areas, which will lead to long waits for ART due to out-of-sequence arrivals at the quay. Therefore, it is necessary to regulate the speed of ART to adjust the timing of ART arriving at the quay. However, existing scheduling systems tend to ignore the impact of ART speed and loading sequence constraints on terminal operations. To optimize the multi-ART control problem of ACT, the waiting time of ART at the quay is taken as the optimization goal, and the speed regulation of ART during each task is defined as a Markov decision process. Then, by incorporating reinforcement learning and a multi-agent approach, an adaptive decision-making method is developed to generate the optimal speed regulation strategy. This method interacts with the multi-agent simulation environment to obtain real-time status information and learns strategies online to improve the intelligence of individual agents and the collaborative capabilities of the agent group. Finally, a multi-agent simulation model embedded with a reinforcement learning agent is established on AnyLogic software. Simulation results show that this method can effectively reduce the waiting time of ART, improve the coherence and efficiency of loading operations, and exhibit good performance in online scenarios that consider emergency tasks. The results indicate that the speed of ART in ACTs with parallel layout of the yard can impact the operational efficiency of the system. Furthermore, by appropriately defining the reward function and training method, collaborative behaviour among equipment can be enhanced, ultimately optimizing the overall performance of the system.

Optimizing multiple equipment scheduling for U‐shaped automated container terminals considering loading and unloading operations

AbstractU‐shaped automated container terminals (ACTs) represent a strategic design in port infrastructure that facilitates simultaneous loading and unloading operations. This paper addresses the challenges of scheduling multiple types of equipment, such as dual trolley quay cranes (DTQCs), automated guided vehicles (AGVs), double cantilever rail cranes (DCRCs), and external trucks (ETs) in U‐shaped ACTs. This paper proposes a mixed integer linear programming model for optimizing the multiple equipment scheduling, aiming to minimize container completion time and AGV waiting time simultaneously. This paper customizes a hybrid genetic‐cuckoo optimization algorithm (HGCOA) with double‐point crossover and Lévy flight Cuckoo search strategies. Extensive numerical results show that the proposed HGCOA outperforms the benchmark genetic algorithms in terms of solution quality and computational time while significantly improving efficiency without substantial sacrifices in solution quality compared with the exact solution method. Overall, this study presents a promising solution for enhancing coordination and operation efficiency in U‐shaped ACTs.

Greening container terminals: An innovative and cost-effective solution for sustainable reefer container storage

This research addresses the critical necessity for energy-efficient solutions in port operations. The primary objective of this paper is to introduce and assess the viability of an innovative infrastructure termed Underground Reefer Container Storage (URCS) devised to mitigate the significant and increasing energy demand posed by reefer containers in ports. This study employs a discrete-event simulation (DES) model to evaluate the feasibility, environmental implications, and cost-effectiveness of three distinctive URCS infrastructure designs. These designs are compared against conventional storage methods to ascertain their capacity for minimizing energy usage and greenhouse gas emissions. The analysis reveals that the best scenario for a specific case study involves a multi-block layout comprising two underground yards, capable of accommodating 39% of the overall refrigerated container capacity at a port. This layout cuts CO2 emissions by 61% from the 2.704 GWh/year energy used by refrigerated containers, yielding around 1.4 million USD/year cost savings. Further analyses using weighted searches to prioritize URCS container slotting led to shorter container dwell times at ports, rendering energy savings 23% higher than in similar unplanned settings. Moreover, this study presents URCS as an eco-friendly alternative for port-based reefer container storage, offering practical alignment with sustainability goals and regulations. The innovative design and its successful application provide holistic insights, paving the way for enhanced port energy management and environmental care. In addition, the implementation of URCS has the potential to reshape port procedures, yielding economic and ecological benefits. This initiative contributes to diminishing the carbon footprint of ports, aligning with global endeavors towards greener and more responsible practices.

Improvement of Container Dynamic Allocation for Automated Container Terminals in the Post-Epidemic Era

Improvement of Container Dynamic Allocation for Automated Container Terminals in the Post-Epidemic Era

Utilizing Amphibious AGVs to Optimize Container Transshipment for Deep Sea and Hinterland Operations

Transshipment is a key component of modern-day shipping logistics. Container supply chains rely on tran-shipment hubs to access remote locations. With globalisation driving growth in container trade, maritime congestion is rising at container terminals in ports worldwide. This is expected to worsen as demand con-tinues to grow. This research explores novel maritime equipment designs that can contribute to solving problems in the trans-shipment chain. One such idea is that of the Amphibious Automated Guided Vehicle, an innovative concept that travels on both land and sea. Envisioned as a tool to minimise the rehandling of containers, the Amphibious AGV forms the heart of the new changes that this research proposes for the fu-ture of trans-shipment. Complementing swifter trans-shipment, the research also proposes complementary design concepts such as floating terminals to add more flexibility for container ships and Amphibious AGVs applied to exchange containers offshore. To validate these ideas, an agent-based modelling methodology was used and replicated in the environment of the Hong Kong- Pearl River Delta. This work, therefore, opens up an intriguing future scope for maritime transshipment that is both sustainable and adaptable while also discussing limitations and concerns that need to be carefully considered.

Energy-efficiency and safety-driven multidimensional evolutionary game for AGVs transportation at automated container terminals

The velocity, acceleration, and number (VAN11VAN: The velocity, acceleration, and number.) of AGVs are crucial factors that impact the efficiency, energy consumption, and safety (EES22EES: The efficiency, energy consumption, and safety.3 ACT: Automated container terminal.) of horizontal transport in automated container terminals (ACT3s). This study utilizes multidimensional and evolutionary game theories to address these factors. Specifically, it considers the probability of AGV fault, treats the resulting faults as input costs, and regards the managers' decision preferences as benefits. According to different strategy combinations, a multidimensional evolutionary game based AGVs transportation model is established to analyze their effects on EES. Stability analysis and numerical simulation show that various strategy choices influence the evolutionary trends in EES of horizontal transportation. The findings demonstrate that reasonably setting the VAN of AGVs in the right range for a certain number of tasks can maximize the benefits of EES. The increases in efficiency and energy consumption benefits would accelerate the modification of velocity and acceleration strategies. The rise in safety benefit would also enhance the probability of adjusting AGV number. As the fault probability increases, the benefits for EES decreases. This study provides management insights into scheduling optimization and strategic adjustment for ACTs.

Unraveling intra-urban freight parking patterns: A data-driven geospatial study of shared logistics sector in Hong Kong

Insufficient urban parking in densely populated cities has led to challenges like traffic congestion and unauthorized parking. While existing literature extensively covers parking behaviors among private vehicles and taxis for commuters, limited research has been proposed centering on urban shared freight activities. It can be problematic to neglect shared freight activities because these logistics activities often require more flexible parking space for goods loading/unloading near urban destinations. This study therefore introduces a geospatial data-driven approach to investigate urban parking behaviors from shared freight activities using GPS trajectories collected in Hong Kong. The analysis involves three main folds: using rank-size distribution and log-odds ratio to comparatively examine spatial heterogeneity of parking, evaluating illegal on-street parking events via illegal parking index, and quantifying relationships between parking behaviors and urban functions using random forest (RF) and SHapley Additive exPlanations (SHAP). The findings reveal significant concentrations of parking events on weekdays/weekends and with different parking durations. Particularly, high illegal on-street parking concentration is reported in Tsuen Wan and Kwai Chung, where the port container terminals and industrial activities are located. We further discover that industrial and dining densities both indicate significantly positive impacts on the relationship to the increases of overall parking frequency and illegal parking index. This study can be of great interest to current parking management and enforcement strategies in cities and relevant practical implications are discussed.

Near real-time nautical depth mapping via horizontal optical fibers and distributed acoustic sensing

Safe navigation in ports and waterways subjected to siltation requires nautical depth monitoring. For this purpose, surveying vessels equipped with a zero-offset echo sounder and intrusive point measurements are frequently used. Because these measurements depend on the availability of a surveying vessel and require access to quay walls, such as at the container terminals in seaports, the temporal resolution is limited. Especially at these locations, a high temporal resolution monitoring system could allow for a higher occupancy rate. We propose to use Distributed Acoustic Sensing to monitor the nautical depth using fiber-optical cables. We install five horizontal fibers at different heights between two points and continuously record along the complete installation. Analysing the continuous recordings, we show that horizontal fibers can be used to monitor the water-mud interface depth with a vertical resolution around six mm. Multiple passive sources, like vessel movements and water currents, are used to estimate the water-mud interface.

Factors affecting on Container Inventory Management (CIM): Evidence from Container depots in Sri Lanka

Container inventory and management (CIM) is an integral part of running a successful container logistics operation, allowing for best-in-class container utilization and low-cost operations. Ineffective container inventory management has become a fairly widespread concern in the shipping industry. carrier's extensive fleet is essentially useless if it is not managed effectively and efficiently. The container inventory can be managed effectively to maintain a smooth balance between supply and demand while reducing potential extra expenses by adhering to efficient and effective procedures. This paper proposes some factors affecting to container inventory management [CIM] in Container depots in Sri Lanka. Accordingly, a target population of 384 senior employees in the field are followed by a questionnaire survey have been carried out and data were analyzed mainly using Chi-Square test. Researcher believes that responses received by employees whom with experience more than 10 years can highly influence on the output of the study based on judgmental sampling method.Data analysis, reliability analysis, demographic factor analysis, descriptive statistical analysis, cross tabulation analysis, and correlation analysis. Chi-square testing and multiple regression analyses were used. With the expertise point of view, this study would lead to understand the factors influence on CIM. After clear analysis, the study concluded four factors namely, demand and supply of containers, high shipping rates, imports and exports trends and cargo seasonality have an influence on the container inventory management. It’s acceptable that no any party can completely avoid such consequences, but the researcher believes that with proper identification and planning accordingly, this ineffectiveness of container inventory management can be lessened or controlled. With no doubt, taking proactive measures will positively impact on container industry of Sri Lanka as well as the economy of the country.

PortLaneNet: A Scene-Aware Model for Robust Lane Detection in Container Terminal Environments

In this paper, we introduce PortLaneNet, an optimized lane detection model specifically designed for the unique challenges of enclosed container terminal environments. Unlike conventional lane detection scenarios, this model addresses complexities such as intricate ground markings, tire crane lane lines, and various types of regional lines that significantly complicate detection tasks. Our approach includes the novel Scene Prior Perception Module, which leverages pre-training to provide essential prior information for more accurate lane detection. This module capitalizes on the enclosed nature of container terminals, where images from similar area scenes offer effective prior knowledge to enhance detection accuracy. Additionally, our model significantly improves understanding by integrating both high- and low-level image features through attention mechanisms, focusing on the critical components of lane detection. Through rigorous experimentation, PortLaneNet has demonstrated superior performance in port environments, outperforming traditional lane detection methods. The results confirm the effectiveness and superiority of our model in addressing the complex challenges of lane detection in such specific settings. Our work provides a valuable reference for solving lane detection issues in specialized environments and proposes new ideas and directions for future research.

Optimization of Berth-Tug Co-Scheduling in Container Terminals under Dual-Carbon Contexts

In order to address the dynamic changes in vessel preferences for berth lines caused by the deployment of shore-based power equipment in major ports and the collaborative scheduling problem of berthing and towing assistance, this paper quantifies the environmental costs of pollutants from the main engines of tugs and auxiliary engines of container ships using an environmental tax. Additionally, considering the economic costs such as vessel delay and shore power cable connection, a two-layer mixed-integer linear programming model is constructed using the task sequence mapping method. This model integrates the allocation of continuous berths at container terminals with coordinated towing scheduling for shore power selection. A solution approach is designed by combining the commercial solver (CPLEX) and the immune particle swarm optimization algorithm (IAPSO). The proposed scheme is validated using the example of the Nansha Phase IV Terminal at the Port of Guangzhou. The results show that compared to the traditional first-come-first-served and adjacent scheduling schemes, the collaborative scheduling scheme proposed in this paper reduces the total cost by 21.73%. By effectively utilizing berth resources and shore power equipment while densely arranging collaborative tasks and appropriately increasing the number of tugs, the port can convert the economic cost of leasing a small number of tugs (increased by 10.63%) into environmental benefits (decreased by 33.88%). This approach provides a reference for addressing nearshore pollution emissions in ports.

Decomposition algorithms for the robust unidirectional quay crane scheduling problems

Our study focuses on a two-stage robust optimization model for the unidirectional quay crane scheduling problem with uncertain handling times at container terminals. We first implement two classical algorithms adopted in Li and Zhang (2021), the Benders decomposition algorithm and the column-and-constraint generation algorithm, to solve the robust model. Based on analytical and numerical comparisons of them, we design an exact hybrid algorithm to leverage capabilities of both algorithms by alternatively adding cuts of both kinds. Extensive experiments validate the effectiveness of this mechanism. Numerical experiments also reveal that the benefit and the cost of robustness fade away as the uncertainty budget increases and highlight the advantage of our robust approach to deal with uncertainty over a two-stage stochastic program under extreme situations.

Evaluating the technical efficiency of Egypt’s main container terminals

ABSTRACT Technical efficiency in container terminals refers to the ability of a port/terminal to operate at maximum capacity with a minimum number of resources. This includes optimising equipment and workforce utilisation, as well as streamlining operations and logistics to reduce delays and increase throughput. This research follows a deductive approach using Data Envelopment Analysis (DEA) models (CCR) and sensitivity analysis (SA) to define the most effective variable in the efficiency score of the main Egyptian container terminals. According to the sensitivity analysis, the most significant variable influencing the efficiency scores is the draft. Using the CCR model, it was found that the majority of the Egyptian container terminals under review were inefficient during the study period, with the exception of the East Port Said terminal. The current research is limited to evaluating the technical efficiency of six Egyptian container terminals (Alexandria, El-Dekheila, Damietta, East Port Said port, Port Said West, and El-Sokhna terminals) using two different DEA models from 2018 to 2022. The present research offers an in-depth approach for evaluating the technical efficiency of container terminals. The study’s findings could be applied to developing guidelines for enhancing the efficiency and productivity of Egypt’s container terminals.