Container Liner Research Articles

Investigating temperature fluctuations in the wine and liquor maritime supply chain from South Africa to the United Kingdom: A case study

This study explored temperature fluctuations in dry shipping containers transporting wine and liquor along maritime supply chains. It also examined how these variations affect product quality, and evaluated the effectiveness of thermal foil container liners in mitigating temperature changes. Temperature trials were conducted from the South African loading depot and concluded at the first distribution centre in the United Kingdom. Ambient temperature sensors were placed on cartons of wine and liquor inside the thermal container liner and between the thermal liner and the door of the container. Weather data was also collected during the trials. Temperature profiles showed large fluctuations in temperature inside containers because of day and night cycles while the containers were stacked at the departure and destination ports, posing challenges for supply chain management. Descriptive statistics were used to analyse the temperature profiles, whereas logit analysis was used to determine the impact of the thermal container liner on the temperatures to which the wine and liquor were exposed. Blind tastings were used to evaluate product quality after exposure to temperature fluctuations. Results showed that thermal liners significantly reduced temperature variability, which is critical for maintaining wine and liquor quality. Despite this, blind tastings confirmed that some products were negatively affected by temperature deviations. The study recommends the use of thermal foil liners for maritime transport of wine and liquor to minimise product damage and financial losses. This finding is particularly relevant for exporters aiming to preserve the quality of their wine and liquor throughout long-distance shipping routes.

Dynamic Flexible Allocation of Slots in Container Line Transport

Due to the imbalance between supply and demand, liner container transportation often faces the problem of low slot utilization, which will occur in the shipping process, such as dry container demand exceeding the available dry slots and reefer slots not being fully utilized. This makes it important and challenging to maintain a balance between the actual demand and the limited number of slots allocated for liner container transport. Therefore, this study proposes a flexible allocation method: expanding the types of containers that can be loaded in the same slot. This method is suitable for handling each dynamic arrival container booking request by shipping enterprises, making decisions to accept or reject, and flexibly allocating shipping slots. In order to maximize the total revenue generated by accepting container booking requests during the entire booking acceptance cycle, we establish a dynamic programming model for the flexible allocation of slots. For model solving, we use the Q-learning reinforcement learning algorithm. Compared with traditional heuristic algorithms, this algorithm can improve solving efficiency and facilitate decision-making at the operational level of shipping enterprises. In terms of model performance, examples of different scales are used for comparison and training; the results are compared with the model without flexible allocation, and it is proved that the model proposed in this paper can obtain higher returns than the model without flexible allocation. The results show that the model and Q-learning algorithm can help enterprises solve the problem of the flexible allocation of shipping slots, and thus, this research has practical significance.

Toward green container liner shipping: joint optimization of heterogeneous fleet deployment, speed optimization, and fuel bunkering

AbstractContainer liner shipping companies, under the international shipping carbon reduction indicators proposed by the International Maritime Organization, must transform two key aspects: technology and operations. This paper defines a green liner shipping problem (GLSP) that integrates the deployment of a heterogeneous fleet, speed determination, and fuel bunkering. The objective is to achieve low‐carbon operations in liner shipping, taking into consideration the diversification of power systems, the use of alternative fuels in ships, and the continuous improvement of alternative fuel bunkering systems. For this purpose, we present a bi‐objective mixed integer nonlinear programming model and develop two methodologies: an epsilon‐constraint approach and a heuristic‐based multi‐objective genetic algorithm. We validate the effectiveness of our model and methods through a case study involving container ships of various sizes deployed on intra‐Asian short sea routes by SITC International Holdings Co., Ltd. The experimental results highlight the crucial role of dual‐fuel (DF) ships in the pursuit of low‐carbon strategies by liner companies, with liquefied natural gas and ammonia DF ships being the most widely used. Additionally, fuel cell (FC) ships, particularly those powered by ammonia and hydrogen, demonstrate significant carbon reduction potential. Furthermore, ships with larger container capacities have a greater cost advantage. For the GLSP, speed determination is an auxiliary decision, and the lowest speed is not necessarily the optimal choice. Decision‐makers must carefully balance competing economic and carbon emission reduction objectives, as deploying more alternative fuel ships may increase fuel bunkering and fuel consumption, resulting in a higher total operating cost.

Analysis of the Liner Shipping Network Structure of the Asia–Europe Main Trunk Route Using Social Network Analysis

Due to COVID-19, the shipping market has faced uncertainty, and the possibility of changes in port routes has increased. The purpose of this study was to analyze the network of container liner shipping routes between Asia and Europe. In particular, this research focused on a global risky situation—the COVID-19 pandemic. The data examined encompassed Asia–Europe route schedules from January 2018 to October 2021, which exhibited significant fluctuations due to the COVID-19 pandemic originating in 2019. To access this problem, utilizing concepts of centrality from social network analysis (SNA), namely degree centrality and betweenness centrality, this analysis incorporated route capacity as a weighted factor. The findings revealed that the port of Rotterdam held the highest degree of centrality in 2018, 2019, and 2021, while Shanghai claimed the highest degree of centrality in 2020. Singapore exhibited the highest betweenness centrality. Asian ports wielded greater influence during the COVID-19 pandemic compared to European ports. Furthermore, Singapore emerged as a pivotal mediator in the Asia–Europe routes, playing a significant role within the global supply chain. Results showed that the port could be put into an unstable situation. Therefore, the managers of port and shipping companies should be ready to minimize risk. From an academic perspective, it is difficult to integrate and analyze container liner schedules as they are monthly updated. This study therefore analyzed continuous schedules to examine dynamic changes in schedules. By adopting SNA, we presented changes in connectivity over multiple periods. This study addressed questions stakeholders may have had about route changes during the global crisis, contributing to sustainable container transportation. This study provides a general understanding of Asia–Europe container scheduling for decision makers. Using market schedules, this research analyzed the connections, and evaluated and compared each port.

Towards decarbonization: How EEXI and CII regulations affect container liner fleet deployment

This study examines the effects of two pivotal maritime regulations, namely the Energy Efficiency Existing Ship Index (EEXI) and the Carbon Intensity Indicator (CII), implemented by the IMO starting from 2023, on the container-fleet deployment. A mixed-integer programming model is formulated to optimize the fleet deployment with considering the constraints of the above-mentioned regulations and the goal of minimizing operating costs. The findings reveal that the CII regulation leads to a substantial decrease in both ship speeds and carbon emissions concurrently, although there may be an uptick in the number of deployed ships. Conversely, the EEXI has a minor effect on speeds due to the prevalence of slow steaming. Based on research findings, several policy implications are elucidated for shipowners.

Enhancement Contrast of Thermograms through Compensating for Uneven Irradiation in Thermographic Testing for Containment Liner Plates

Enhancement Contrast of Thermograms through Compensating for Uneven Irradiation in Thermographic Testing for Containment Liner Plates

International Practice of Liner Container Shipping Regulation in the Transport System

Effective regulatory and legal framework in this field has several positive advantages for the transportation participants. A significant place in the article is given to ensuring the principle of “common carrier” for access of a wide range of consumers to the container carriers service. In connection with the transformation both of supply chains and logistics flows under conditions of new foreign economic factors along with the emergence of new shipping lines on the Russian container market the relevance of this topic will continue to increase.Aim. To consider the aspects of normative and legal regulation of liner container shipping in the USA, EU, PRC and the Russian Federation.Tasks. To analyze the strategies of shipping lines on the Russian and global markets, to identify key regulatory legal acts of foreign countries in the sphere of liner container shipping, to identify the features of the Russian legislation in this sphere and the ways of its development.Methods. Regulatory legal acts of the USA, EU, PRC and the Russian Federation were collected, which play an extremely important role in the development of international container transportation and increasing the competitiveness of foreign economic activity.Results. The research of relevant legal frameworks and instruments of state regulation of sea container lines activity to ensure non-discriminatory access of consumers of transportation services, public availability of information about liner container services, high quality of transportation services for foreign economic relations was carried out.Conclusions. In modern foreign economic conditions, alliances and various forms of carrier cooperation are the subject of state regulation of liner container shipping in order to protect competition on the market. The legislation of the USA and the Russian Federation establishes compulsory publication of shipping line tariffs, while according to the provisions of the PRC legislation shipping lines provide their tariffs to the freight exchange, which is authorized by the competent state body. In addition, international experience shows that sea lines “Common carriers” are subject to a number of other requirements. In the Russian Federation, sea container transportation is carried out by both liner and tramp vessels due to the fact that the certain carriers are not registered as shipping line operators and information about some regular container services is limited.

ROBUST OPTIMIZATION MODEL OF CONTAINER LINER ROUTES IN FEEDER LINE NETWORK

The universal application of the hub-and-spoke maritime network makes feeder line network key to restricting the quality and efficiency of maritime transportation. However, container liner routes in feeder line network are susceptible to the changes in shipment demand and international fuel prices. Therefore, based on the hub-and-spoke maritime network, this paper constructs a robust optimization model of container liner routes in feeder line network. Under the capacity and time constraints, routes optimization and ship equipment under uncertain environment are analysed. An improved tabu search algorithm was designed based on the characteristics of the model. The example analysis proves that the model can still ensure the robustness of routes under uncertain environment, which is more applicable than the deterministic model.

Analysis of the Impact of Large Container Ships on Port Capacity

Facing the fierce competition in the shipping market, major container liner companies are constantly increasing the scale of container ship construction in pursuit of scale effect, and the trend of large-scale development of container ships is increasingly obvious. The enlargement of container ships not only intensifies the competition of shipping companies, but also brings profound changes to the port's facilities and equipment. This paper analyzes the development process, background and reasons of the large-scale container ships, as well as the future development trend of large-scale ships. The qualitative and quantitative method was used to analyze the current status of ship enlargement on the development status. Through the corresponding data and cases, combined with the current rise of international trade protectionism and the global spread of new pneumonia, the impact of ship enlargement on port development was analyzed with a view to the port Development provides corresponding theoretical references and suggestions.

Concrete ablation depth analysis of OPR1000 NPP during top flooding ex-vessel cooling

This study assesses the integrity of OPR1000 nuclear power plant (NPP) containment during top flooding ex-vessel cooling in the event of a postulated severe accident. Maintaining containment integrity during ex-vessel cooling is critical for preventing substantial release of radioactive materials to the environment. To analyze the feasibility of top flooding ex-vessel cooling of the OPR1000 NPP, the spread of molten corium in the dry reactor cavity is first calculated, followed by calculating the concrete ablation depth according to the reactor cavity flooding delay time. It is judged whether the leak-tightness integrity of the containment during ex-vessel cooling is maintained based on whether the containment liner plate (CLP) is damaged or not. In the first step analysis, the spread of molten corium in the dry reactor cavity is calculated using computational fluid dynamics (CFD) methodology for various cases, and results indicate a uniform deposition of approximately 143 tonnes of molten corium, with a thickness of about 33 cm, meaning that the thermal load is distributed uniformly in the reactor cavity. In the second step analysis, concrete ablation depths are calculated base on the delay time for flooding the reactor cavity. For the postulated severe accident, injecting coolant into the reactor cavity one hour after breach of the reactor vessel results in a concrete ablation depth of about 0.74 m, indicating no damage to the CLP and ensuring containment integrity. The maximum allowable delay time for flooding the reactor cavity for the postulated severe accident is evaluated to be 2.24 hours maintaining the leak-tightness integrity of the OPR1000 NPP containment. The research methodology and findings presented in this study are expected to aid in assessing the feasibility of top flooding ex-vessel cooling and establishing appropriate accident management strategies for nuclear power plants like the OPR1000 NPP.

A two-step approach for deploying heterogeneous vessels and designing reliable schedule in liner shipping services

Schedule reliability is a crucial metric for measuring liner container shipping service. Due to the inherent uncertainties at sea and ports, schedule delays and unreliable on-time performance have long plagued shipping companies. In practice, the heterogeneity of container vessels also creates challenges for deployment and schedule optimization. To address the problem, we develop a two-step approach with two programming sub-models. In the first step, we tackle the challenges of ship deployment and scheduling by considering heterogeneous vessels and capturing the interarrival time between adjacent ports of call. In the second step, we use the conditional value-at-risk (CVaR) to address the uncertainty risk avoidance in schedule design. To solve the stochastic programming models, we employ a solution framework based on the outer linear approximation method and the risk measure method, where CVaR is specified as the risk measure. We illustrate the application of our model on a case study concerning a real route operated by COSCO Shipping Lines. The results show that the total cost of liner shipping service with heterogeneous fleet on the route can be reduce by 4.77% compared with homogeneous fleet. And the cost of risk with the reliable schedule can be decreased by 8.04% compared with the ideal schedule. The research conclusions can provide some useful decision-making references for shipping companies to deploy heterogeneous vessels and design reliable schedules.

Changes in vulnerability of global container shipping networks before and after the COVID-19 pandemic

To explore the changes in vulnerability of global container shipping networks before and after the COVID-19 pandemic, this study presents a novel method for identifying the critical collapse point of the global container shipping network based on geospatial connectivity changes and network collapse process under the deliberate attack. Additionally, we propose a quantitative approach to assess the trends and degree of changes in network vulnerability. To accomplish this, we construct the global container shipping network for 2015, 2017, 2019, and 2021, utilizing port and route statistics of the top 100 global container liner companies for analysis. The outcomes indicate that the global container shipping network's tolerance to deliberate attacks was 7.98%, 8.52%, 9.57%, and 9.72% in 2015, 2017, 2019, and 2021, respectively, implying that the global container shipping network continued its trend of gradual strengthening before the COVID-19 pandemic, but with a relatively low change in tolerance of 1.57%. The factors influencing the changing vulnerability of the global container shipping network before and after the COVID-19 pandemic include declining port efficiency, shorter and more trans-regional routes, and retaliatory increases in global container shipping trade. Ultimately, we provide relevant policy recommendations to continuously secure the global container shipping network's interconnectivity.

Dynamic container slot allocation for a liner shipping service

In this paper, we study a dynamic container slot allocation problem (DCSAP) for a liner container shipping company that aims to make an acceptance or rejection decision to each dynamically arriving container slot booking request. To capture the dynamic arrival feature and real-time acceptance/rejection decision of the booking request, we formulate the DCSAP as a dynamic programming (DP) model with the objective of maximizing the total revenues generated by accepted container booking requests over the entire booking horizon. Due to the well-known curse of dimensionality of solving a DP model, we develop a series of models to transform the intractable DP model into a solvable approximate linear programming (ALP) model. We further propose a spatiotemporal-heterogeneity-based (STH-based) decomposition preprocessor by identifying the spatiotemporal property of the DCSAP before solving the ALP model. Extensive numerical experiments are conducted to assess the applicability of the developed research methodology.

Quantitative Investigation of Containment Liner Plate Thinning with Combined Thermal Wave Signal and Image Processing in Thermography Testing

Quantitative Investigation of Containment Liner Plate Thinning with Combined Thermal Wave Signal and Image Processing in Thermography Testing

Liner shipping network design model with carbon tax, seasonal freight rate fluctuations and empty container relocation

In response to the challenges posed by the shipping carbon tax resulting from the low-carbon environmental policy, the seasonal fluctuation of freight rates in the container liner shipping market, and the reduced flexibility in fleet adjustment, we develop a bi-level programming model to maximize the average revenue per container ship and the total revenue of the fleet.The upper-level model selects the optimal shipping networks for both the off-season and peak season, while also designing the liner fleet for these two networks. The lower-level model optimizes the slot allocation scheme and the empty container storage and transportation scheme to evaluate the revenue of the network calculated by the upper-level model. Three meta-heuristic algorithms are proposed. We take the China-West Europe liner shipping route as the research object, and conduct numerical experiments on different optimization objectives and liner types. Results demonstrate that maximizing the average revenue per container ship involves reducing the carbon tax cost, simplifying the trunk route structure, and increasing the number of feeder routes. These changes lead to reduced satisfaction rates for transportation demands in both China and Europe. If the company seeks to maximize total revenue, they may achieve the opposite result. Therefore, liner companies should reasonably set optimization goals, adjust the network structure and liner operation status in a timely manner, and scientifically allocate container ship and empty containers to achieve the operational goals of reducing carbon emissions and maximizing revenue to cope with the volatile market and the low-carbon regulations.

Dynamic pricing and competition of container liner shipping services in a duopoly spot market

With the application of online booking technology in the spot market of container liner shipping, dynamic pricing is considered an important tool and development trend to balance container shipping supply and demand from the spot market. This study examines the dynamic pricing and competition of container liner shipping services in a duopoly spot market where two shipping companies compete on liner routes with multiple overlapping origin–destination (O-D) pairs. The demand within the spot market for one shipping company is sensitive to both the freight rate set by the shipping company and its competitor. To tackle this complex challange, a non-linear mixed-integer generalized Nash equilibrium optimization model was formulated for the dynamic pricing and competition problem to maximize the profits of both shipping companies. To effectively reach the optimal solution for the dynamic pricing and competition problem, the proposed model is reformulated as a linear complementary problem with a Karush-Kuhn-Tucker (KKT) conditional system. An optimal response decomposition algorithm is developed to obtain the global optimal solution of the model. Numerical experiments with the Trans-Pacifc shipping network of two oligarchic shipping companies were conducted to demonstrate the efficiency of the solution algorithm and the applicability of the proposed model in improving the two companies’ profits from the spot market.

A two-phase optimization model for low-sulphur operation of container liners in the context of carbon neutrality

The shipping industry is under significant pressure to reduce carbon emissions, and it is crucial to ensure that current efforts to reduce sulphur dioxide (SO2) emissions do not result in increased carbon dioxide (CO2) emissions. Against the background of carbon neutrality and sulphur emission control area (SECA) policies, this paper proposes a two-phase mathematical model to study the impact of liner low-sulphur compliance operation on carbon emissions. The model addresses four key problems: fleet deployment (phase Ⅰ); compliance option decisions, speed optimization and cargo allocation (phase Ⅱ). To solve these problems, a novel dual population evolutionary algorithm has been designed. The results show that implementing low-sulphur compliance operations for liner companies does not simultaneously reduce both total costs and CO2 emissions, and the rise in the price of low-sulphur oil, the preference for cost decision-making and the expansion of SECAs will increase CO2 emissions; the current sulphur limit policy needs to be adjusted urgently to implement the carbon neutrality goal of the shipping industry; government subsidies can reduce CO2 emissions to some extent, but low-carbon or zero-carbon alternative energy is an inevitable choice for achieving carbon neutrality in the shipping industry.

Pricing of Contractual Shipments and Slot Allocation in Container Liner Shipping under Stochastic Environment

Pricing of Contractual Shipments and Slot Allocation in Container Liner Shipping under Stochastic Environment

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.

Quantification of the Effective Detectable Period for Concrete Voids of CLP by Lock-In Thermography

This study is to inspect the voids between the concrete containment building and the containment liner plate (CLP) in the light-water reactor type nuclear power plant with lock-in thermography (LIT) inspection technology. For that, a finite element method (FEM) model containing concrete voids was created, and the thermal distribution change of the CLP surface was simulated through numerical analysis simulation of various LIT inspection conditions and converted with real-time thermography data. For the simulated temperature distribution image and the amplitude and phase images calculated by the four-point method, the signal-to-noise ratio (SNR) is analyzed based on the sound area and void areas. As a result, the difference in SNR according to the size of voids was remarkable, and the effective detectable period (EDP), which was common to each inspection condition, was derived. Furthermore, a CLP concrete mockup identical to the model shape is produced, and the thermal image of the EDP is analyzed through the experiment with the same analysis technique, and the results are compared. Although there are some differences between the numerical analysis conditions and the experimental environments, the deduction and utilization of EDP through FEM simulation are considered useful approaches to applying LIT to inspect concrete voids on the back of the CLP.