Container Port Research Articles

A hybrid container throughput forecasting approach using bi-directional hinterland data of port

Accurate forecasting of port container throughput plays a crucial role in optimising port operations, resource allocation, supply chain management, etc. However, existing studies only focus on the impact of port hinterland economic development on container throughput, ignoring the impact of port foreland. This study proposed a container throughput forecasting model based on deep learning, which considers the impact of port hinterland and foreland on container throughput. Real-world experimental results showed that the proposed model with multiple data sources outperformed other forecasting methods, achieving significantly higher accuracy. The implications of this study are significant for port authorities, logistics companies, and policymakers.

The Impact of a New Container Port on the Greenhouse Gas Pollution

Abstract Background Large vessels that call at European ports will have to pay for their CO2 emissions from transporting cargo that enters or goes from a European port since January 2024. The costs will increase with increasing global trade. This results in a higher pollution level, including greenhouse gas (GHG) emissions like CO2. Methods/ Approach Based on the gravity model embedded in a global supply chain, we developed a model to evaluate maritime transport pollution in case a new, sufficiently large container port becomes operational. Additionally, we consider how lousy railway connections to European customers increase transportation costs and pollution. Results The approach to the well-connected sequences of gravity models in the intercontinental maritime chains evaluates the differences in quantities of cargo between ports when a new port is opened, and the waiting time does not change. We also highlight that poor rail connections can reduce this positive effect. Conclusions We showed how it is possible to estimate the optimal capacity of a new port with a multi-level gravity model and how this would affect the pollution around the port and on the routes from the port to the final consumers.

The effects of tropical cyclone on the container shipping network: A case study of typhoon Ma-on (2022)

As climate change intensifies, tropical cyclones pose increasing challenges to container shipping networks (CSN). However, research related in this area remains insufficient. In this study, we analyzed the effects of Typhoon Ma-on on the CSN using over 776 million Automatic Identification System (AIS) trajectory signals. Our findings reveal that the typhoon not only altered the network structure of the CSN but also affected the importance of container ports, vessel flow, and travel distance fluctuations along shipping routes. After the typhoon, the recovery of the network’s connectivity and stability, as well as travel time fluctuations, was less robust compared to other aspects. Additionally, the impact ranges for port importance, vessel flow, and travel distance fluctuations were 1,750 km, 500 km, and 2,250 km, respectively, following an inverse distance decay pattern. These findings offer new insights for stakeholders to enhance the effectiveness of disaster prevention and mitigation policies.

Hierarchy and mobility of Latin America and Caribbean container ports

Research on port hierarchies within a maritime region is crucial for comprehending the dynamics of seaborne trade and the broader trends within the maritime sector and related supply chains. This study investigates the evolution of the Latin America and the Caribbean (LAC) container ports and regional sub-systems from 2000 to 2022, analyzing traffic dynamics, shifts in port throughput rankings, and market concentration trends in and among the different coastal regions. Conceptually, this analysis benefits from the notion of evolutionary phases, revealing the stages of a port system's development. Methodologically, 49 LAC ports of international interest are categorized into different coastal regions and tiers based on throughput sizes. Various metrics, including the Gini coefficient, Lorenz curve, Herfindahl-Hirschman Index (HHI), and Kendall Tau (τ), assess port hierarchy and related mobility since 2000. The observed shifts in the hierarchy and market structures, coupled with the fluctuating positions of critical ports, underscore the transition that LAC container ports dynamics experienced in the 21st century. Following a particularly dynamic and volatile evolution observed in the 2000s, the financial crisis of 2008/09 was a critical juncture leading to the transition of the LAC port dynamics from the ‘emerging’ to the ‘maturity’ phase. On the contrary, the pandemic (2019) has not affected the pre-existing hierarchy or the moderate market concentration that was already in progress. The LAC region comprises port sub-systems (coastal ranges) subjected to different tendencies towards (de)concentration, yet mobility in port rankings within each sub-system decreases. The study also reveals the coexistence of this transition with a structural transformation of port governance structures, i.e., granting of concessions of operations to third parties. In 20 of these ports and the above-average mobility of ports are operated by Global Terminal Operators (GTOs), and calls for further research on the (non) causality of these phenomena.

Integrated optimization of vessel dispatching and empty container repositioning considering turnover time uncertainty

The global trade disproportion results in the accumulation of containers in import-dominated ports and shortages in export-dominated ports, causing congestion and high freight costs, thus hindering maritime shipping economy development. To address these issues, this study develops a stochastic programming model considering uncertain container turnover times. The model integrates decisions for vessel deployment and empty container repositioning over multiple planning periods through a two-stage decision process, aiming to minimize the total cost, including vessel deployment, container leasing, and penalty costs for unfulfilled demand. By formulating the scenario selection problem as a p-median problem, we effectively reduce the model size. We propose an accelerated Benders decomposition algorithm which leverages the independence of sub-problems in the second stage to enable parallel computation. Numerical experiments show that our Benders decomposition algorithm improves solution speed by over 63% compared to the Gurobi optimization solver. Furthermore, our integrated optimization approach proves to be more cost-effective than the reactive method used by shipping lines, achieving an average cost savings of 0.72%. Additionally, our method of constructing turnover time scenarios to address uncertainty saves approximately 0.45% in costs compared to using the probability distribution of container turnover time.

Design procedure of reach stacker control system

Reach stackers are efficient and maneuverable machinery for an overload of overall containers in cargo terminals and ports today. Such machinery design determines the practical interest of the engineering industry specialists. However, the lack of information in open sources about structural or kinematic diagrams of equipment control mechanisms and recommendations for their calculation does not allow an effective approach to the creation and update of reach stackers. We developed the design procedure of the reach stacker control system, which considers the kinematic and geometric parameters of the container spreader, as a result of the conducted research. It can be used in the design stages of mechanisms for spreader lateral displacement, extension of the spreader sections, spreader inclination in the vertical plane, container fixation by spreader, spreader rotation, lifting-lowering and telescoping of the boom, as well as during the real operation modes of reach stackers in cargo terminals and ports.

Optimization berth allocation in container terminals: A Pyomo and Google Colab approach

Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.

The effect of internal and information integration on Oman container ports’ operational performance: The mediating role of supply chain management practices

This study aims to investigate the relationship between internal and information integration within the supply chain (SCI-INTI and SCI-INFI), supply chain management (SCM) practices, and port operational performance (POP) in Oman’s container ports. Additionally, it explores the mediating role of SCM practices in the relationship between SCI-INTI, SCI-INFI, and POP in Oman. To meet the study’s objectives, a quantitative cross-sectional survey method was used. A total of 377 questionnaires were distributed to managers responsible for supply chain operations in the main departments at Sohar and Salalah ports, yielding 331 usable responses, with a response rate of 88 percent. The data collected were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that both internal and information integration within the supply chain have positive and statistically significant effects on the operational performance of Oman’s container ports (POP). Specifically, Supply Chain Integration with Internal Integration (SCI-INTI) significantly impacts POP (β = 0.249, t = 5.039, p < 0.001), and Supply Chain Integration with Information Integration (SCI-INFI) also significantly affects POP (β = 0.259, t = 4.966, p < 0.001). Additionally, SCI-INTI positively influences Supply Chain Management Practices (SCMP) (β = 0.381, t = 7.674, p < 0.001), as does SCI-INFI (β = 0.484, t = 9.878, p < 0.001). Furthermore, SCMP positively and significantly influences the operational performance of Oman’s container ports (β = 0.424, t = 7.643, p < 0.001). These findings contribute to the literature by emphasizing the significance of internal and information integration within the supply chain and SCM practices as strategic internal resources and capabilities that enhance operational performance in container ports. Understanding these elements enables decision-makers and policymakers within government port authorities and port operating companies to optimize internal resources and capabilities to improve port operational performance.

Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments

Efficient truck dispatching strategies are paramount in container terminal operations. The quality of these strategies heavily relies on accurate and expedient simulations, which provide a crucial platform for training and evaluating dispatching algorithms. In this study, we introduce data-driven machine learning methods to enhance container port truck dispatching simulation accuracy. These methods effectively surrogate the intersections within the simulation, thereby increasing the accuracy of simulated outcomes without imposing significant computational overhead in sparse data environments. We incorporate three data-driven learning methods: genetic programming (GP), reinforcement learning (RL), and a GP and RL hybrid heuristic (GPRL-H) approach. The GPRL-H method proved the most efficacious through a detailed comparative study, striking an effective balance between simulation accuracy and computational efficiency. It reduced the error rate of simulation from approximately 35% to about 7%, while also halving the simulation time compared to the RL-based method. Our proposed method also does not rely on precise Global Positioning System (GPS) data to simulate truck operations within a port accurately. Demonstrating robustness and adaptability, this approach holds promise for extending beyond port operations to improve the simulation accuracy of vehicle operations in various scenarios characterized by sparse data.

Processes and mechanisms of the evolution of container port system in the Yangtze River Delta: An analysis from spatial and network perspectives

the Yangtze River Delta (YRD) has established a large-scale container port system with seaports and Yangtze ports as the mainstay and including other riverports and dry ports, occupying a prominent position in the pattern of national and even the global shipping development. Considering the new trend that the theoretical paradigm of port research has shifted from “spatial” to “network”, and that the focus of research goes from seaports to both seaports and inland ports, this study brings the complexity and uniqueness of the development of the port system in the YRD into the picture. By analyzing the influence of globalization, specialization, marketization, transportation, and greenization on port system development and its pattern formation, this paper elaborates on the gradient process of transportation and services allocation from the coast to the riverside and then to the inland. The evolution of port system is considered to have a temporal gradient between spatial-level transportation expansion and network-level services upgrading, and it is also believed that there is a spatial gradient in logistics supply chain terminalization between coastal and inland areas. Combined with the quantitative analysis from 200 5 to 2020, after entering the stage of port regionalization in the YRD, the container volume is distributed from coastal concentration to inland decentralization at the spatial level, while at the network level, port and shipping service enterprises (PSSEs) maintain a relatively centralized distribution along the coastal areas. At the same time, container volume growth rate fluctuates down, number of PSSEs growth rate fluctuates up, which trend is notable in the seaport. Currently, port regionalization in the YRD is still incomplete; the degree of logistics supply chain terminalization of ports in inland areas is relatively low; and the synergy between spatial and network in the entire YRD region has not yet been formed. This study tries to answer the question of the relationship between different types of ports in the complex port system, which can enrich the theoretical and empirical results of port system research and guide the practice of port and shipping in the YRD.

The Moderating Effect of Stakeholders Management on the Relationship Between Organizational Characteristics and Performance of African Ports

The main objective of this study was to determine the moderating effect of stakeholders’ management on the relationship between organizational characteristics and the performance of seaports in Anglophone Africa. This study adopted a positivist research philosophy with a descriptive cross-sectional census survey design. Structured questionnaires were employed to collect primary data targeting executive managers of container-handling seaport terminals in Africa who are knowledgeable in port operations and management. Additional published data was also obtained from the websites of some of the ports. The response rate was 83.6%. The reliability and validity of the indicator items were ascertained through diagnostic tests. The use of SRMR and NFI confirmed model fitness. Partial Least Squares Structural Equation Modeling using Smartpls 4.0 software was used for data analysis and measurement model estimation to test the null hypothesis that there is no significant moderating effect of stakeholders’ management on the relationship between organizational characteristics and the performance of seaports in Africa. The finding established a positive and significant moderating effect of stakeholders’ management on the relationship. The study concluded that sound and competent stakeholders’ management enhances port container terminal performance thereby creating a competitive advantage for ports in Anglophone Africa. The study adds to new knowledge, theory, policy, and practice by recommending that seaports in Africa should mitigate possible conflicts from stakeholders while developing new ports or expanding existing ports by embracing stakeholder theory.

Dynamic tugboat deployment and scheduling with stochastic and time-varying service demands

Container ports serve as crucial logistics hubs in global supply chains, but navigating ships within such ports is complex due to restricted waterways. Tugboats play a critical role in ensuring safety and efficiency by escorting and towing ships under these conditions. However, the tugboat deployment and scheduling problem has received little attention. To fill the research gap, we propose a new research problem - the dynamic tugboat deployment and scheduling problem, in which not all requests are confirmed initially but dynamically confirmed over time and future tugging demands need to be anticipated when managing the utilization of tugboats. To formulate the problem, we propose an extended Markov decision process (MDP) that incorporates both reactive task assignment decisions and proactive tugboat waiting decisions, creating a reactive and proactive MDP. To solve the advanced MDP model efficiently for real-time decisions, we develop an anticipatory approximate dynamic programming method that incorporates appropriate task assignment and waiting strategies for deploying and scheduling a heterogeneous tugboat fleet and embed the method into an improved rollout algorithm to anticipate future scenarios. The effectiveness, efficiency, and performance sensitivity of the developed modeling and solution methods are demonstrated via extensive numerical experiments for the Singapore container port.

Digital twin-driven proactive-reactive scheduling framework for port multi-equipment under a complex uncertain environment

The pervasive uncertainties in multiple port equipment scheduling frequently result in container handling delays or ineffective plans. To address the complexities and uncertainties of port multiple equipment integrated scheduling problem, this paper introduces a Digital Twin-driven (DT-driven) proactive-reactive scheduling framework for the first time. This framework is designed to promptly respond to uncertainties in the scheduling process and provide a transparent visualization of operational information. It specifically tackles the integrated scheduling problem of port quay cranes, Intelligent Guided Vehicles (IGVs), and yard cranes, considering uncertainties such as fluctuations in operating time, equipment failures, and IGV route conflicts. By developing a virtual container port simulation, which features a U-shaped port layout and double-cycling mode drawn from real-world scenarios, the paper evaluates the proposed framework's effectiveness. The experimental results demonstrate that the digital twin framework method significantly improves efficiency and conserves energy. Additionally, in large-scale conditions, the makespan difference between the DT-driven approach and the non-DT-driven approach is as much as 19.56 %. In terms of energy consumption savings, the DT-driven approach's scheduling plan can save 3.67 % of energy consumption under large-scale conditions. Moreover, as the fluctuation index increases, the energy consumption savings become even more significant. This paper also discusses the potential implications of adopting this framework for port companies, highlighting its benefits in enhancing operational and energy efficiency and its incorporation into port management systems. The sensitivity analysis can offer guidance to port companies on optimal equipment allocation strategies.

En-route recharging scheduling strategy for electric trucks serving inter-terminal container transportation

ABSTRACT Container ports are increasingly deploying electric trucks (ETs) for inter-terminal transportation (ITT). However, en-route recharging activities, which reduce ITT efficiency, are necessary for ETs because of limited battery capacity. This study proposes a real-time strategy to schedule the en-route recharging activities for ETs. The strategy dynamically monitors the ITT system, and simultaneously designates charging piles for ETs and determines their positions in the service sequences. An ET may be designated to a remote but shorter-queued pile. The total queue time of the ETs served by a designated pile can be reduced by adjusting the service sequence. The effectiveness is demonstrated in comparison with an alternative strategy in a real-world case. The results indicate that the proposed strategy effectively reduces container throughput time by 21.8% and ET energy consumption by 12.3%. Sensitivity analyses suggest that the strategy is applicable for ports with multiple charging stations and moderate ET fleet size.

Adaptation planning of container ports in the context of typhoon risks: The case of Ningbo-Zhoushan port in China

This study conducts a comprehensive survey of the risk of typhoon to container ports by assessing the risk level of typhoons in China's major container ports, predicting their economic losses, and evaluating corresponding adaptation measures. It analyzes adaptation measures in response to typhoon impacts, with a case study of Ningbo-Zhoushan port, one of China's most representative regional ports. It identifies the inadequate supply of institutions and the absence and misbehavior of the main port stakeholders as the main cause of varying institutional imperfections in the port adaptation system. This study contributes to the development of efficient port typhoon prevention policies, reduction of economic losses and casualties, and improvement of port operational efficiency. It also fills an important research gap on climate risk and adaptation in China's container ports, with an emphasis in enhancing port resilience.

Resilience of regional container port network: based on projection correlation and dynamic spatial Markov Chain

ABSTRACT Ports are interconnected by shipping routes within the global logistics network. Shocks and risks stemming from financial crises, epidemics, ecology, and so on have prompted shifts in cross-border labor division towards regional cooperation, reflecting an ‘anti-globalization’ trend. Despite these dynamics, few studies have analyzed the spatial structure and dynamic evolution of resilience within regional container port network. Addressing this gap, this study considers spatial and dynamic attributes to identify influential factors of resilience and introduces the concept of spatial lag-multidimensional resistance (SL-MR) to strengthen the understanding and cognition of regional container port network resilience (RCPNR). By ports in Tianjin and Hebei, China, it constructs a dynamic spatial Markov chain (DSMC) based on the projection correlation (PC index) to dissect transition trajectories amid financial crises and other conflicts. The findings indicate: (1) The regional container port network often experiences a low-level path dependence like ‘poverty trap.’ (2) Hierarchical spatial lags significantly influence the transition probability of container port network resilience degradation, with regional port relationships being unidirectional rather than cooperative. (3) The impact of the 2008 financial crisis and the COVID-19 pandemic on regional port resilience varies, serving as key determinants in shaping diverse resilience types.

Factors Influencing Greenhouse Gas Reduction Measures in European Ports: Implications for Sustainable Investing

European Union cargo and container ports are under pressure to reduce GHG emissions and achieve carbon neutrality by 2050, as mandated by the European Commission. The pace of progress varies among ports. This study examined the characteristics influencing GHG reduction measures in European cargo and container ports and their implications for sustainable investing. The methods used in this study, such as linear regression models to analyze predictive variables, can be applied in sustainable investing to assess which factors most strongly predict a company’s environmental, social, and governance performance. Using linear regression models to analyze data from the 33 busiest European ports, we identified five predictive variables: port size, cargo mix, surrounding population density, access to the sea, and the economic wealth of the host country. Our findings revealed that the port size significantly correlates with the adoption of measures to reduce scope 1, 2, and 3 emissions. This study underscores the importance of contextual and operational factors in evaluating sustainability efforts across sectors. The results contribute to drawing parallels with the field of sustainable investing within finance. This offers valuable insights for sustainable investing, emphasizing the importance of considering various contextual and operational factors when evaluating the sustainability efforts of entities in different sectors.

PENERAPAN METODE HIRARC UNTUK ANALISIS RISIKO KESELAMATAN KERJA PADA CONTAINER CRANE DI PELABUHAN PETI KEMAS BITUNG

The causes of work accidents can come anytime, anywhere and to anyone. The risk can be fatal or just a minor accident, depending on the level of opportunity. To minimize the number of work accidents, it is necessary to take anticipatory steps from both the workers and the company management. This research focuses on reducing the impact of work accidents by analyzing the risks of hazards that can occur in every job. Researchers research using the HIRARC method for efforts to prevent and reduce the potential for work accidents, avoid and minimize risks that occur appropriately by avoiding and minimizing the risk of work accidents and controlling fiber in order to carry out the activity process so that the process becomes safe. Based on the results of hazard identification, there are 9 sources of danger on the container crane at Container Port of Bitung with 1 hazard risk has a high risk level (H) / High, 6 hazard risks have a high risk Moderate (M) / Medium, and 2 hazard risk has a high risk level Low (L) / Low. Keywords : K3, Loading and Unloading Process, HIRARC.

A new model for multi-port berth allocation problem based on an improved genetic algorithm

Port integration can enhance operational efficiency and service level in response to heightened competition among container ports. Nevertheless, container ports are still considered independent systems separately in formulating scheduling plans. This research explores a new multi-port berth allocation problem (MPBAP) with continuous berth layout considering the mutual influence between ports. The MPBAP is compared with the single port berth allocation, and effects of different numbers of vessels continuously berthing at all ports on a single route on the MPBAP are discussed through vessel operation rate. The problem is formulated by a mixed integer programming model by minimising the total port stay time of all vessels. The quay is highly discretised and a GA coupled with parallel computing is applied to accelerate the search for the optimal model solution. A case study is conducted on two adjacent container ports located along the Yangtze River. Results show that multi-port coordinated scheduling is efficiency and the total port stay time of all vessels reduces by an average of 2.63% under the MPBAP. With more than four vessels berthing continuously at two ports on a single route, the MPBAP shows a higher vessel operation rate and the rate gap between the two models exceeds 2%. The approach suggested in this study can enhance the port system’s efficiency and provide a new idea for coordinated scheduling in other port groups.

Multicriteria Decision Model for Port Evaluation and Ranking: An Analysis of Container Terminals in Latin America and the Caribbean Using PCA-TOPSIS Methodologies

In recent years, despite a decline in international trade and disruptions in the supply chain caused by COVID-19, the main container terminals in Latin America and the Caribbean (LAC) have increased their container volumes. This growth has necessitated significant adaptations by seaports and their authorities to meet new demands. Consequently, there has been a focused analysis on the performance, efficiency, and competitiveness, particularly their most relevant logistical aspects. In this paper, a multi-objective hybrid approach was employed. The Principal Component Analysis (PCA) technique was combined with the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) to rank LAC container terminals and identify operational criteria affecting efficiency. The analysis considered all input variables (berth/quay length, quay draught, yard area, number of quay cranes (portainer), number of yard cranes (trastainer), reachstacker, multicranes, daily montainer movement capacity, number of station reefer container type, number of terminals, and distance to the Panama Canal) and output variable (port performance expressed in TEUs from 2014 to 2023). The results revealed noteworthy findings for several terminals, particularly Colón, Santos, or Cartagena, which stands out as the main container port in LAC not only in annual TEUs throughput, but also in resource utilization.