Container Port Research Articles

Analysis of empty container management

Shipping containers are known as a crucial equipment for global trade. Most of their lifespan containers are spending empty, being in process of repositioning or sitting in a yard. Increasing trade imbalances globally set up empty container logistics as one of the main concerns in container shipping industry. In line with that issue, this paper will analyse the roots of empty container imbalance and port congestion, emphasizing the importance of proper empty container management and challanges which appear along the way. Results of the research show that there is room for improvement while dealing with management of empty containers which primarly implies a cognition of the imbalance problem and long-term predictions as well as mutual cooperation of all parties involved. Furthermore, new solutions and higher level of digitalization will be required to succesully and efficiently handle today’s challanging situations. Reducing empty container transport to a minimum is the key point, where foldable containers and container interchange between carriers can greatly contribute. Efficiency of empty container management must be reflected in increased environmental sustainability throughout the shipping process.

The impact of Brexit on supply chain cost and Ro-Ro traffic at Dover

ABSTRACT This study analyzes the potential impact of Brexit on port congestion and supply chain cost using the example of the largest European Ro-Ro port of Dover. A microscopic simulation model is constructed to replicate traffic conditions and analyse different scenarios. The results show that the current port infrastructure will have difficulties facing the challenges that Brexit could have brought. Checkpoints for border controls are found to be the primary bottleneck. Three types of countermeasures are discussed and found that none of the single measures is sufficient. However, the combination of two additional border checking booths and 10% traffic reduction is the most realistic and effective solution to contain the congestion. The case study shows the company’s supply chain costs would increase by around 7% to 20% in different scenarios. The largest increase comes from annual shipping cost, which accounts for 94% of the total supply chain costs. Alternative transportation options are discussed. It is found that the Port of Dover remains the preferred Ro-Ro port, but the Lo-Lo container port of Southampton will become a better solution for cargoes with modest unit value.

Railway access optimization for a container port in the high-speed railway era - a case study in China

ABSTRACT The expansion of high-speed railway (HSR) has opened up new freight capacity on traditional railway (TR) lines in China. In order to increase China's railway volume of containers transported to port terminals, this paper estimates the HSR and TR modal splits for passenger transport. Then, the TR capacity used for passengers is calculated via traffic assignment model, and the number of passenger trains on TR lines is estimated and then deducted from total TR capacity. The remaining balance gives the freight capacity of a TR line. Moreover, a bi-level programming model is built to optimise the location of railway freight terminals and the corresponding train dispatching frequencies in a case in which trains on TR lines and trucks on highways are both used to transport containers to port terminals. The ports of Shanghai and Ningbo with their hinterlands are used as a case study for numerical analysis.

Two-sided sustainability: Simulating battery degradation in vehicle to grid applications within autonomous electric port transportation

The provision of frequency containment reserves (FCR) by electric vehicles in an autonomous port transportation system is a way to stabilize power grid frequency. However, the Vehicle-to-Grid (V2G) service's additional charging processes lead to faster degradation of vehicles' batteries. How much the FCR provision affects battery life (BLD) and what degradation costs are incurred depends on specific application conditions. Therefore, this study demonstrates the application of a V2G system for a port container terminal. In the analysis, vehicles' charging processes with and without FCR provision are simulated within the degradation model developed for this case, and relevant degradation factors are determined by applying the Rain-Flow Counting (RFC) method. Overall, three degradation models are discussed concerning their fit for the case at hand. Results indicate that Cycle-Count Models best represent battery degradation, showing an increase in battery degradation of 1.36% through the use for FCR. This supports improved business case simulations to enable two-sided sustainability models by stabilizing the electric grid and enabling electric transportation in ports simultaneously.

Innovation in Smart Ports: Future Directions of Digitalization in Container Ports

New digital Industry 4.0 solutions and smart applications are being adopted in many industries, also in the most advanced ports in the world. Still, it is not clear in which directions digitalization in ports will develop in the future. Building on the research literature and the state-of-the-art in major container ports, this research characterizes smart ports and Port 4.0 with three key focus areas: automation, sustainability and collaboration. Following the scenario building theory, this article constructs four alternative scenarios for future smart ports and shows the ways in which these alternative scenarios will lead to different prioritization of digital innovations between automation, sustainable development and cooperation issues. This will have a big impact on what digitalization in ports will be like in the future.

Logistics Costs for Seaborne Trade in Nigeria: An Empirical Study

Seaports are fundamentally connectivity points in the global economic system, especially container ports, which are supportive and well-connected to major global trade routes. Regular and dependable services from shipping are critical to lowering the costs of trade, particularly transportation expenses, integrating supply chains, and enabling global trade. For Nigeria, trade costs seem to be an impediment to international trade development, and improving trade logistics performance is crucial to enhancing nations' trade acceptability. Field surveys were conducted in some selected seaports and outward environments, and hypotheses were examined in order to assess the cost-effectiveness and efficiency of the ports' facilities and activities. The result revealed that logistics costs, customs effectiveness, quality of infrastructure, government policies, and logistics service deliveries have significant effects on the development of seaborne trade in Nigeria. Therefore, institutional improvements will lower logistics costs, providing opportunities to expand seaborne trade, and benefit consumers worldwide through competitive freight costs.

Prediction of Operation Time of Container Ship at Berth under Uncertain Factors Based on a Hybrid Model Combining PCA and ELM Optimized by IPSO

With the rapid development of global trade, the turnover of shipping containers has increased rapidly. How to use port resources reasonably and efficiently has become one of the main challenges that ports need to deal with when planning for the future. In order to develop scientific and efficient berth plans to improve operational efficiency and service level, this paper proposes a hybrid prediction model based on Principal Component Analysis (PCA) and Extreme Learning Machine (ELM) optimized by Improved Particle Swarm Optimization (IPSO), namely, the PCA-IPSO-ELM model. After assessing the uncertain factors influencing the operation time of the container ship at berth, this work reduces the dimensionality of the investigational data by the PCA method. Aiming to solve easy premature convergence of the traditional particle swarm algorithm, this paper introduces an improved particle swarm optimization algorithm via dynamic adjustment of nonlinear parameters. This improved particle swarm algorithm is mainly used to optimize the weights and thresholds of the extreme learning machine. Thus, a PCA-IPSO-ELM model which aims to forecast the operation time of a container ship at berth, is constructed. Using the historical operation data of the Tianjin Port Container Shipping Company as the prediction sample, this PCA-IPSO-ELM model is compared and assessed with traditional models. The results show that compared with other models, the PCA-IPSO-ELM prediction model has the characteristics of high prediction accuracy, fast running rate and strong stability, and it has a higher coefficient of determination and a better fitting degree.

Quay crane scheduling with time windows constraints for automated container port

The traditional quay crane of the container terminal is gradually transitioning to automation, which significantly changes the loading and unloading operation mode of the quay crane. In this paper, we study the sequence scheduling of automated quay crane (AQC) with time window constraints. First, the process of AQC handling operation is decomposed, and the mechanism model for AQC operation is established. Then, a mixed integer linear programming model is formulated to optimize the scheduling of AQC considering the time window constraints. Finally, the effectiveness of the optimization model is verified by arithmetic examples, and the management insights of energy efficiency optimization of the quay crane scheduling are given through scenario analysis.

Quay-Yard operation analysis of port container terminals in Nigeria

This paper presents significant measures to tackling berth occupancy and quay-yard operation problems. Case study was conducted on a port container terminal in Nigeria confidentially identified as ‘Port A’ in this paper. Hungarian assignment algorithm was used to reduce the total travel time of the yard trucks from an average of 6.4 minutes to 3.5minutes, while M/M/c/K queuing model was applied in scheduling the quay crane assignments. Results showed tremendous increase in quay crane rate, berth capacity and improved berth utilization. Also, for the reach stacker, the crane rate can be improved to 30 TEUs/hr at berth occupancy below 0.40 with TEUs factor of 1.4. These results imply that for Nigeria terminals operating with reach stacker crane, it is possible to improve the berth capacity without affecting the berth utilization of the terminal.

A New Mathematical Model for Container Stacking in Seaport Terminals: Case Study

Maritime transport is the operation of moving goods from one place to another by sea. It takes into account the loading and unloading of containers in ports. Once the vessels arrived at the quayside, they are unloaded by means of quay cranes and then transferred to the storage or transshipment areas. The Container Stacking Problem (CSP) is one of the major problems in seaport terminals, in particular in view of the considerable increase in the number of containers and the limitation of storage areas in the container ports. It has a considerable impact on the efficiency of port operations. In this paper, we propose a new mathematical model for determining the exact storage locations of incoming containers in the storage zone in order to minimize the total travelling distance from the quay to the storage location. The suggested model takes into account different types of containers. It has been validated based on the real case study of the Tunisian Sfax seaport. The obtained results are promising and the storage responsible is satisfied with the reached solutions.

Container port performance assessment: a nonnegative matrix factorization approach

Container port performance assessment: a nonnegative matrix factorization approach

Research on the Beibu Gulf Port Container Terminal Operation System Construction Performance Evaluation Based on the AISM-ANP

With the continuous development of smart ports, the construction of port information systems has become the construction focus of the future development of such ports. However, the existing performance evaluation system for port information systems represents a research gap. It cannot effectively achieve specific improvement in the construction of information systems for port services and capabilities. In this paper, an evaluation index system was forged from the three perspectives of the operating level, management capability, and economic efficiency. As a first step, starting from the current situation of Beibu Gulf Port (Port B) construction, the three dimensions of the evaluation index system were determined using the scheme of literature review, questionnaire research, and fieldwork. Additionally, through adversarial interpretive structural modeling (AISM), it is concluded that the port loading and unloading operation capability and service level are the fundamental factors for measuring the construction performance of the container terminal operation system (CTOS). The results are used as input to construct an analytic network process (ANP) model to obtain the index weights. Finally, the gray clustering method (GCM) is introduced to construct a quantitative evaluation model to quantitatively evaluate the construction performance of the Port B CTOS. The quantitative benefits brought by the construction of the CTOS are finally verified. The scores of the corresponding dimensions of the port before and after the construction of the CTOS system in Beibu Gulf Port are obtained experimentally. The conclusion shows that the construction of CTOS makes the port operating level module improve the most, from 40.023 to 70.733 points; at the same time, it is found that two aspects, i.e., green security and economic benefits, in current construction are directions requiring further work in future port construction. Finally, a visualized quantitative analysis and evaluation method for the performance of smart port construction is proposed.

Estimation of CO2 emissions for ship activities at container port as an effort towards a green port index

The International Maritime Organization has adopted regulations to reduce emissions by 50% by 2050 in the maritime sector. Several strategic recommendations have been issued to achieve an environmentally friendly and low emission concept. Greenport is an environmentally friendly port concept with low emissions from every movement and activity. The objective of this paper is to estimate the CO2 emissions contributed by container ships based on their activities in the container terminal. The estimation method used is a bottom-up model by considering engine power, load factor, and fuel emission factor. Three ship activities during berthing have been analyzed i.e., maneuvering activities, waiting in the port basin, and berthing conditions. From the emission estimation results, it is found that berthing activities contribute to emissions of up to 69% of the total ship activities at the container port. The results of CO2 emissions by container ship are estimated at 1.58 kg/DWT.

Hub port choice and shipping connectivity in Southeast Asia during COVID-19 pandemic: implications for post-pandemic competition landscape

ABSTRACT The COVID-19 pandemic has had a major impact on the container shipping and port industry in terms of its reach and scale. The research analyzes the impact of COVID-19 on hub port choice and shipping connectivity using the case of major container ports in Southeast Asia. This study enriches the definition of connectivity and proposes a new research approach that differentiates the order of port-call for mainline services. The research approach is applied to the case of major container ports in Southeast Asia for the Asia-Europe trade route. The study further analyzes hubbing strategies of major shipping lines and alliances with the application of data mining on global satellite ship data. Findings indicate shipping connectivity to have grown in Singapore particularly at the expense of Port Klang during the COVID-19 pandemic as evidenced by changes in the shipping networks of The Alliance and Ocean Alliance. The research offers important policy and managerial implications concerning the post-COVID competition landscape covering the aspects of joint venture terminals, shipping alliance networks, and container port development.

Optimization of Multi-Port Empty Container Repositioning under Uncertain Environments

Empty container repositioning has always been an important problem faced by ports. In this paper, we study the multi-port empty container repositioning problem with the uncertainty of the demand and supply of empty containers in ports. First, we established an optimization model for empty container reposition strategies and calculated every port’s proportion, depending on its own empty container storage, on the operation of other ports and on the leasing company, in meeting the demand. Next, we established an optimization model for the empty container non-repositioning strategy, calculated the same proportions and compared their performance under two strategies. A two-stage particle swarm optimization (TS-PSO) algorithm was designed to solve the two models, and an example was used to verify the effectiveness of the algorithm and the rationality of the two models. Our research showed that the total cost of empty containers, storage costs, lease costs and the optimal storage of empty containers in ports under the repositioning strategy are all lower than those of the non-repositioning strategy. The proportion of the empty container demand met by inventory under the repositioning strategy is higher than that under the non-repositioning strategy, while the proportion of the empty container demand met by leasing is lower. The costs of leasing cost and repositioning empty containers are higher than those under the non-repositioning strategy. The increase in transportation time between ports per empty container mainly leads to the increase in the reposition costs of all ports. The increase in storage fees chiefly leads to the rising storage costs of all ports. The increase in leasing fees leads to the rising leasing costs of all ports. The paper provides a method for ports to decide the upper limit of empty container storage and to optimize their repositioning strategy.

Traffic in a nursery: Ship strike risk from commercial vessels to migrating humpback whales (Megaptera novaeangliae) in a rapidly developing Australian urban embayment

The rapid recovery of the Australian humpback whale (Megaptera novaeangliae) population and parallel increase in maritime traffic, has increased the spatial overlap between whales and vessels in Australian waters. Ship strike is a recognized global anthropogenic source of mortality or injury to large whales, and a potentially increasing risk in Australia. However, our understanding and evaluation of this threat to humpback whales around Australia, is hindered by the lack of seasonal whale distribution data in high marine traffic areas. Here, we present five consecutive years (2017–2021) of both north and south migrating humpback whale distribution data to quantify the relative risk of ship strike based on the co-occurrence with commercial ships in Moreton Bay. This marine embayment is home to Australia’s fastest growing container port (The Port of Brisbane) and has recently been identified for its ecological importance to this migrating species. We quantified co-occurrence by multiplying predicted whale and ship densities together to estimate both intra- and inter-annual ship strike risk. Ship strike risk increased during the humpback whale’s southern migration (September-October), coinciding with a substantial habitat shift into the Bay during this time. Groups containing calves were a predominant pod type in Moreton Bay. Given their increased vulnerability to ship strike, this study underscores the need for immediate and effective mitigation actions, such as seasonal vessel speed reductions as well as mariner education and outreach programs.

Development of a Machine Learning-Based Framework for Predicting Vessel Size Based on Container Capacity

Ports are important hubs in logistics and supply chain systems, where the majority of the available data is still not being fully exploited. Container throughput is the amount of work done by the TEU and the ability to handle containers at a minimal cost. This capacity of container throughput is the most important part of the scale of services, which is a crucial factor in selecting port terminals. At the port container terminal, it is necessary to allocate an appropriate number of available quay cranes to the berth before container ships arrive at the port container terminal. Predicting the size of a ship is especially important for calculating the number of quay cranes that should be allocated to ships that will eventually dock at the port terminal. Machine learning techniques are flexible tools for utilizing and unlocking the value of the data. In this paper, we used neighborhood component analysis as a tool for feature selection and state-of-the-art machine learning algorithms for multiclass classification. The paper proposes a novel two-stage approach for estimating and predicting vessel size based on container capacity. Our proposed approach revealed seven unique features of port data, which are the essential parameters for the identification of the vessel size. We obtained the highest average classification accuracy of 97.6% with the linear support vector machine classifier. This study paves a new direction for research in port logistics incorporating machine learning.

Resilience Strategies of Ports against Covid-19 in Terms of Chaos Theory

During the Covid-19 pandemic, all sectors experienced chaotic dynamics worldwide. For example, maritime transport, particularly ports as one of its main elements, had to continue operating in this chaotic environment. Ports developed their own strategies to provide resilience against these challenges. However, any study in the related literature has not been reached that reveals resilience strategies of ports by combining literature review and interviews with port practitioners. As a novelty of the study, it was tried to evaluate resilience strategies of ports by grounding chaos theory. Therefore, this study had two aims: (1) identifying the Covid-19 strategies of Turkish container ports; (2) prioritizing these strategies in terms of impact level. First, interviews were conducted with Turkish container port representatives to find out their resilience strategies. These strategies were then validated with a literature review and new ones were detected. Second, separate relation analyses of the strategies were conducted for the interviews and literature. Finally, ports’ resilience strategies against Covid-19 disruptions were prioritized using Fuzzy Analytic Hierarchy Process (AHP) based on the port managers’ evaluations. Fuzzy AHP is widely used and accepted in the maritime business literature. This method also diminishes inconsistencies and subjective evaluations by employing fuzzy logic. The results showed that ‘Control Mechanism’, ‘Hygienic Measures’, and ‘Information Exchange’ were the most effective resilience strategies. By using chaos theory, this study helped to theoretically clarify the role of port management approaches to the challenges of the Covid-19 pandemic. These findings can therefore guide container port practitioners in overcoming pandemic conditions.

Club convergence and allometry in Chinese mainland coastal container ports

Research on container port development is of great theoretical and practical significance because of the port's crucial role in the local economic system and regional transportation system. Understanding the development dynamics of container ports is important when formulating related operational and management strategies in the future. Hence, this article investigates the club convergence of 25 coastal ports in mainland China spanning from 2006 to 2020 in terms of container throughput, which signals the development of a port to some extent. The study finds three clubs in China's coastal container port system, with various transitional behaviors indicating that the whole system has shown a tendency toward a slight centralization since 2013 and that small and medium-sized ports are regressing. On this basis, analysis on the container port system is conducted by employing an allometric model. The result shows that allometric relations indeed exist not only among three factors linked with port development, namely, port container throughput, port city's import-export volume, and port maritime connectivity, but also among the three port clubs. Moreover, the allometric relations slightly differ and vary over time for the three port clubs, thus implying that large ports may have different growth mechanisms from small and medium-sized ports. Based on the findings mentioned above, several general policy implications are proposed, which may impact port production, construction, and operations management in mainland China.

Impact of Second-Tier Container Port Facilities on Drayage Operation

Background: An increasing number of container and chassis staging, “dray-off”, drop yard, and depot facilities are being established outside of North American marine container terminals. The increased use of these “second-tier” facilities implies that there must be some capacity, delivery time, service, or reliability benefit that offset the additional cost and complexity. Methods: This paper builds on the previously developed integrated drayage scheduling model to determine the impact of second-tier port facilities on drayage operation. It modifies the previously developed model by incorporating the following features: (1) trucks do not have to wait at customers’ locations during the import unloading and export loading operations; (2) drayage operations can include a drop yard (i.e., second-tier facility) for picking up or/and dropping off loaded containers outside the marine container terminal; and (3) a customer is allowed to request any of the following jobs: pick up an empty container, pick up a loaded container, drop off an empty container, and drop off a loaded container. Results: The results indicated that by moving the location of import pickup and export delivery from inside the marine container terminal to a location outside the terminal, the efficiency of drayage operation could increase. Additionally, when import pickup and export delivery take place inside the marine container terminal, the most efficient location for the chassis yard and empty container depot is inside the terminal. However, when the location of import pickup and/or export delivery are outside the terminal, the most efficient location for the chassis yard and empty container depot is also outside the terminal. Conclusions: The modeling results suggest that in addition to adding reserved capacity for marine terminals or as buffers to reconcile the preferred delivery times of importers, the second-tier facilities could also yield operational savings. However, the potential drayage efficiencies depend heavily on shorter queuing and turn time at these less-complex facilities compared to marine container terminals. Lastly, the modeling results suggest that the observed evolution of North American marine container terminals from self-contained entities into multi-tier systems is likely to continue to add additional capacities to accommodate container trade growth. This finding has important implications for regions and communities concerned over the impact of growing container ports.