Port Disruptions Research Articles

Evolution and stability of liner shipping networks in Northeast Asia from 2018 to 2022

Ports are severely challenged by the uncertainty of the transportation environment. To evaluate the stability of maritime transportation network in Northeast Asia under port disruption, a network stability analysis model based on node failure rate that considers static and structural, dynamic and functional is proposed in this paper. In this model, the stability of the maritime transportation network is redefined. Based on complex network theory, the statistical topological parameters and evolution of the network are quantitatively analyzed. The active response and passive adaptation process of the maritime transportation network to the failure rate of the port are analyzed. The evaluation results illustrate that the initial stability of the port is proportional to the non-redundant connections and independence of the port. Network location advantages profoundly affect the probability of port failures. The diffusion of port failures in maritime transportation is phased, and the network is adaptive to port disruptions and has high stability. These results contribute to better planning of maritime transportation routes and strategies for port calls by strategic planners of shipping companies.

Liner shipping network vulnerability to component disruptions: A China-Europe container flow analysis

This study conducts a vulnerability analysis of the China-Europe liner shipping network, including all relevant liner shipping services and China Railway Express services. The standard multicommodity network flow model is extended to assess network vulnerability and the relative importance of ports and services by simulating container flow redistribution in various disruption scenarios. The results show the network is highly resilient to both individual port disruptions and individual service disruptions. Additionally, the distinct shipping network structures of the three shipping alliances result in varying degrees of vulnerability, highlighting the significance of diversified market suppliers in enhancing the overall network resilience. Specifically, the Ocean Alliance is vital in facilitating China-Europe trade, especially along the Mediterranean route, and is more resilient to individual port disruptions.

Managing port disruption through sailing speed optimization for sustainable maritime transportation

Ports, as nodes in maritime transportation, frequently face disruptions leading to congestion, adversely affecting the efficiency and sustainability of the global supply chain. This study considers the speeding-up strategy to alleviate port congestion. We model the transportation network as a closed Jackson network and adopt a tailored mean-value analysis algorithm to solve the model. To deliver the increased sailing speed, we further put forward a bi-section search algorithm. Our numerical analysis results demonstrate the feasibility of increasing speed to alleviate port congestion. However, when port congestion exceeds a certain threshold, the system faces collapse, rendering the increase in speed ineffective. Additionally, we recommend shipping companies consider using clean energy when employing the speeding-up strategy to mitigate congestion, thus safeguarding the environment. Our study combines theoretical methodologies and analytical models, providing insights regarding speeding up the vessels. The findings of this study offer guidelines for real-world sustainable maritime practice.

Ship coping strategies for hurricane-induced port disruptions

PurposeDisruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.Design/methodology/approachThis paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.FindingsThe results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.Originality/valueSince the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

Optimization Model for Container Liner Ship Scheduling Considering Disruption Risks and Carbon Emission Reduction

In the context of economic globalization and the development of information networks, container liner transportation plays a crucial role in international trade. However, the inherent inflexibility of fixed schedules in liner operations poses challenges to the decarbonization of shipping and the stability of liner networks. Therefore, this paper focuses on the impact of port disruptions on route operations, develops a mixed integer nonlinear programming model considering fuel costs, recovery costs, and carbon emissions, and designs a hybrid evolutionary algorithm to solve the proposed model. The research findings indicate that scheduling strategies based on increased vessel speed, the adjustment of port calling sequences, and transshipment leasing after port skipping can effectively reduce the recovery costs after disruption events while meeting freight demand. When a disruption duration is less than 96 h, acceleration strategies and the adjustment of the port calling sequence are favorable choices. When the disruption duration exceeds 96 h, transshipment leasing after port skipping is a feasible solution to ensure the on-time delivery of cargo. The shifting of disrupted port position restricts the selection of scheduling strategies, particularly for ports located at the intersections of routes, which incur higher recovery costs. The implementation of carbon taxes affects the overall operating costs of liner companies, and an appropriate carbon tax level can constrain carbon emissions and ensure the sustainable development of the shipping industry.

An analysis on the resilience of the European port network

Resilience measures based on topological indices from graph theory are proposed to measure three essential aspects of the network resilience, namely connection extent measured by the extent of nodal connection, connection efficiency measured by the connection time aspect, and connection scale measured by service capacity aspect. Real liner service data are utilized to capture the intrinsic structure of the intra-Europe port network and measure its resilience against three potential “attack strategies”. We conclude that the intra-Europe network has a low resiliency towards potential port disruptions as it relies heavily on a few large ports, and is highly sensitive to the easiest human-led attack strategy or a regional natural disaster surrounding the German port region. Also, Piraeus port is found to hold a critical role in the network connection. Another interesting port is Bremerhaven which provides unique connections to many small ports in the network. This study has important political and managerial implications, especially for Europe facing a new era of high uncertainties and continuous turbulences.

Assessing the efficiency and vulnerability of global liner shipping network

AbstractGlobal liner shipping network (GLSN) constitutes an essential part of global maritime supply chains, but it could be vulnerable to disruptions. This paper develops an integrated framework for assessing the efficiency and vulnerability of GLSN. Specifically, a novel efficiency metric is proposed to quantify the performance of GLSN, and the framework enables modeling different levels of port disruption scenarios. Results show that the overall GLSN is quite robust under the partial disruption scenario of any single port (or of any single country's ports), but the damage to different countries is highly heterogeneous. Under dismantling scenarios where the identified most critical ports (countries) are successively disrupted, the GLSN vulnerability increases non‐linearly with an increasing level of disruption. Our findings demonstrate that it is necessary to monitor and protect the identified critical ports (countries); especially, avoiding their simultaneously complete disruptions is of vital importance to the robust functionality of GLSN.

Regional economic losses of China's coastline due to typhoon-induced port disruptions

Port based transportations are key elements governing the operation of global maritime logistics. In China, the southeast coastline suffers from typhoons frequently every year and causes many disruptions to port operations and thus economic losses. Quantitative evaluation of coastal ports' economic losses induced by typhoons is quite demanding and can serve as guidance for port operation planning and disaster prevention. In this paper, a framework based on a hybrid wind numerical model for assessing the direct and indirect economic losses of coastline caused by typhoon-induced extreme wind is proposed. The estimation of port disruptions and their durations is realized based on the typhoon hybrid wind numerical model. For the direct economic losses, this model considers losses to the port based on the loading/unloading operations of containers. The disruption days and economic losses of 31 ports along China's coastline are selected. These include ports from the Bohai Rim Port Cluster, Yangtze River Delta Port Cluster, Southeastern Coastal Port Cluster, Pearl River Delta Port Cluster, and Southwestern Coastal Port Cluster. The analysis takes the record of typhoons from 2006 to 2020 for this investigation. The influence of time-varying variables on economic losses, such as economic growth rate, has been considered. For the indirect economic losses, the input-output models of 11 different provinces (or municipalities) are employed to analyze each sector. Features of adopting a climate model in the economic evaluations are discussed.

Investigation of berth allocation problem in container ports considering the variety of disruption

While a variety of disruptions are involved in the daily operation of container ports, the disruption management process in practice highly relies on the port operators’ experience or follows simple service rules. A need exists for a systematic way to adopt mathematical models to deal with these uncertainties. Considering the significance of the berth in the ports, we investigate the berth allocation problem (BAP) involved with different disruptions from a proactive perspective. We propose a mathematical model and an algorithm that can help operators make robust berth allocation schedules in a more maneuverable way instead of relying on their working experience. The research is presented in the following steps: initially, potential port disruptions related to the BAP are identified; then, based on the identification process, a proactive optimization model is formulated to generate baseline berth allocation schedule, minimizing the baseline schedule cost in the deterministic situation and the recovery cost in the disruption scenarios; finally, due to the characteristic of the BAP, a multi-stage heuristic algorithm is developed to solve large-scale problems. Algorithmic solutions to randomly generated computational instances are compared with the CPLEX solver to validate the reliability and the effectiveness of the algorithm. The difference in the recovery cost and the total cost between the proactive model and a deterministic model shows that the proposed model can generate berth allocation schedules of better robustness and maneuverability that help in practice.

Impact of local port disruption on global container trade: An example of stressing testing Chinese ports using a D-vine copula-based quantile regression

In the shipping market, ports are increasingly interconnected in the global container network. A port disruption in one place can lead to a chain effect on subsequent ports. Nowadays, China's container port throughput accounts for around 30% of the global port throughput, manifesting its essential role in the global container trade system. Therefore, any disruption in Chinese ports could have a cascading effect on the world container trade. This study explores the potential impact on the container main trading lanes given a stress scenario for a number of Chinese ports. We are particularly interested in the degree of risk spillover to the different trading lanes. The stress scenario used in this study is a severe drop in the container throughput in major Chinese ports. This drop will be reflected in quantiles of the respective throughput distributions that are close to zero. D-vine copula-based quantile regression is used to measure the throughput impact of stressed Chinese ports as covariates on other response container trading routes. Copula is a powerful tool to measure the tail dependence structure between throughputs of major Chinese ports and major container trading routes. Results show that port disruptions in China severely impact the major container trading routes. The Asia to Sub Saharan Africa route is extremely vulnerable to downside risk given any port disruption event in China. We have also compared the results with the historical trade and port call data. The results provide significant implications for container shipping risk management.

A methodology for evaluating the economic risks of hurricane-related disruptions to port operations

Among natural disasters, hurricanes pose significant threat to port infrastructure in the United States, especially to those along the coasts of the Atlantic Ocean and the Gulf of Mexico. The operational continuity of ports is critical because of the growing reliance of domestic and international businesses on ports and their significance in the growth of national and regional economies. While direct physical damages to ports are not rare, a shutdown of port operations is more likely declared by authorities as a precautionary and preparatory measure during hurricanes. Considering the enormous economic importance of ports and their vulnerability to hurricanes, the current study proposes a framework and methodology to analyze the economic risks of such hurricane-related shutdowns using hurricane- and port-related determinants. The risks of shutdowns are modeled using regression analysis based on historical port shutdown data and are combined with extensions of the well-known input–output model to predict the operational and economic risks of ports to hurricanes. The application of the methodology is demonstrated by conducting a case study based on the Texas Port System to evaluate the economic risks of hurricane-related port disruptions on the U.S. economy. • Presents a methodology to estimate economic risks of hurricane-related port shutdowns. • The duration of hurricane-related port shutdowns is predicted using regression models. • Economic impacts of port disruptions are predicted using input-output model.

Ships’ response strategies to port disruptions caused by hurricanes

This paper studies ships' operational proactive strategies during the entire process of port disruptions due to environmental factors such as hurricanes. For the first time, the incompleteness and uncertainty of information, and the characteristics of port disruptions are considered. The problem is modeled as a nonhomogeneous Markov decision process (MDP), where different operational actions, such as sailing speed adjustment, handling rate adjustment, and port sequence adjustment are considered. The rolling horizon decision-making approach and a PSO-GA-based hybrid evolutionary algorithm are combined to solve the model. The results show that compared to the strategy without planned schedule adjustments, cost-saving up to 78.34% can be achieved by simultaneously adjusting the sailing speed, cargo handling rate, and port sequence. Counter-intuitively, we find that observing more complete hurricane information or having accurate forecasts does not always conducive to better decision-making. We also find the integration of multiple response strategies yields synergistic benefits. These findings will deepen our understanding of the impact of port disruptions and provide theoretical support for the decision-making of ship's response strategies.

Optimising the resilience of shipping networks to climate vulnerability

ABSTRACT Climate extremes are threatening transportation infrastructures and hence require new methods to address their vulnerability and improve their resilience. However, existing studies have yet to examine the climate impacts on transportation networks systematically rather than independently assessing the infrastructures at a component level. Therefore, it is crucial to configure alternative shipping routes from a systematic perspective to reduce climate vulnerabilities and optimise the resilience of the whole shipping network. This paper aims to assess the global shipping network focusing on climate resilience by a methodology that combines climate risk indicators, centrality analysis and ship routing optimisation. The methodology is designed for overviewing the climate vulnerability of the current and future scenarios for comparison. First, a multi-centrality assessment defines the global shipping hubs and network vulnerabilities. Secondly, a shipping model is built for finding the optimal shipping route between ports, considering the port disruption days caused by climate change (e.g. extreme weather) based on the climate vulnerability analysis result from the first step. It contributes to a new framework combining the global and local seaport climate vulnerabilities. Furthermore, it recommends changing shipping routes by a foreseeable increase in port disruptions caused by extreme weather for climate adaptation.

Socioeconomic impacts of resilience to seaport and highway transportation network disruption

• An integrated transportation-socioeconomic impact model is developed and applied. • Aggregate and distributional impacts of port-transportation disruptions are simulated. • Resilience tactics can substantially reduce potential GDP losses. • Losses from port disruptions increase income inequality . • Port resilience tactics reduce inequality from port disruptions. An integrated transportation-socioeconomic model is developed to analyze the economic consequences of and resilience to seaport and associated transportation network disruptions. Since such disruptions can affect people in a region unequally, the model is constructed to analyze both aggregate economic impacts and impacts across socioeconomic groups. We illustrate the model’s usefulness in a simulated earthquake scenario affecting the Ports of Los Angeles and Long Beach. Total GDP losses from port disruptions, highway transportation cost increases, and general building damages, working through regional and interregional supply-chains, are estimated at $24.2 billion in the Port Region and $30.2 billion in the U.S. as a whole. A combination of several resilience tactics is estimated to reduce GDP impacts by 41.3% in LA and 57.6% in the U.S. The distributional analysis indicates the extent to which lower-to-middle-income groups are more proportionally impacted by port disruptions and middle-to-higher-income groups are more impacted by building damages.

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Impact of Port Disruption on Global Container Trade: An Example of Stressing Testing Chinese Ports Using a D-Vine Copula-Based Quantile Regression

Impact of Port Disruption on Global Container Trade: An Example of Stressing Testing Chinese Ports Using a D-Vine Copula-Based Quantile Regression

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Regional Economic Losses of China's Coastline Due to Typhoon-Induced Port Disruptions

Ships’ Response Strategies to Port Disruptions Caused by Hurricanes

Ships’ Response Strategies to Port Disruptions Caused by Hurricanes

Economic impact of typhoon-induced wind disasters on port operations: A case study of ports in China

The impact of a port disruption can reverberate across the entire economy through global supply chains. It is essential to ensure the regular operation of seaborne transportation considering all risks. Climate events create challenging risks that need to be carefully addressed. This paper proposes an approach to evaluate the economic losses due to port disruptions caused by typhoon-induced wind disasters. Four Chinese ports and their historical typhoon and cargo throughput data from 2007 to 2017 are taken as examples. A wind model is introduced to analyze the wind fields of typhoons. The likelihood of port disruption is then estimated based on the simulated wind field results at each port. Based on the estimated number of port disruption days and daily cargo throughput, the total economic loss of each port is calculated by considering the reputational loss, loss to the shippers, loss to the carriers, and loss to the ports. Finally, the economic impact of port disruption caused by the typhoon-induced wind disasters on port operations in China is discussed. The results suggest that both the disruption time and throughput are critical in economic estimations and the major component of the overall cost is the loss to the shippers. The proposed method directly reflects the typhoon-induced wind disaster-related risks quantitatively encountered at ports, which could help port managers make optimal decisions in controlling port operations.