Container Liner Research Articles

Numerical assestments of maximum depressurisation rate for polymer materials under high-pressure hydrogen

Hydrogen containers type IV should stand for severe operational conditions, such as temperature variations from −40 °C to 85 °C, and depressurisation from high-pressure above 95 MPa to near atmospheric pressure. There are experimental studies showing that container's liner, usually a thermoplastic material, can suffer blistering and buckling during depressurisation process. It has also been proved that elastomers under high-pressure conditions, which are submitted to a rapid depressurisation, can suffer the formation of cavities because of the dissolved gas. The formation of microscopic defects in thermoplastic materials because of rapid depressurisation is less common in scientific literature.In this paper, we evaluate by numerical means the maximum depressurisation rate a polymer sample can stand before cavitation occurs. By studying the influence of geometrical and pressure conditions, so as material's properties, we obtain algebraic equations that define maximal depressurisation rate. Results of present work serve to estimate performance of liner materials, with the scope of safe and fast container discharge.

Defect Imaging Enhancement through Optimized Shape Factors of the RAPID Algorithm Based on Guided Wave Beam Pattern Analysis.

In this study, a modified imaging algorithm was implemented to improve the imaging accuracy for defects located on a structure. Based on analysis of the Lamb wave mode, a guided ultrasonic wave inspection technique was applied, which was able to illustrate images of defects in a 6 mm steel plate simulating containment liner plate (CLP) in nuclear power plants. The dominant Lamb wave mode was determined through short-time Fourier transform waveform analysis and imaging verification. Following tomography verification, limitations of the antisymmetric mode in the thick steel plate were identified. In addition, a modified shape factor, based on the energy distribution factor according to the beam pattern and beam width, was suggested for field applications and improved imaging accuracy. Results of the analysis revealed a beam skewing phenomenon for the Lamb wave mode. In the case of S0 2.7 MHz·mm, skewing as well as distortion effects are not observed in the experiment, while the S0 modes at 2.64 and 2.74 MHz·mm show either of them. Considering skewing width, the size of the shape function was modified. Application of the modified shape function allows us to obtain more accurate image to actual defect shape.

Does vertical integration lead to horizontal collusion in container transport chains?

ABSTRACT With the promotion of mode cooperation and integration in international trade transport in the context of intense globalization, vertical integration between container ports and liners, two key players in container transport chains, often leads to horizontal collusion between container ports. By establishing an infinitely repeated game with discrete time periods, this paper explores the interrelation, the possibility and the stability of the coexistence between vertical integration and horizontal collusion. Our primary finding is that vertical integration and horizontal collusion have mutually reinforcing effects. In particular, the former results in an increase in shippers’ surplus at the expense of the latter.

Shipping industry's sustainability communications to public in social media: A longitudinal analysis

Except for the catastrophic accidents that have made headlines, public's knowledge about the shipping industry remains limited. As a result, the public may form an unjust stereotype of the industry as ‘polluting’ and ‘unsustainable’, which reduces the industry's attractiveness to its potential employees and indirect customers (i.e. end-consumers). It is high time for the industry to shape its public image by not only acting sustainably but also communicating the same to the public. Thus, this study examines the shipping industry's sustainability communications in social media focusing on the Twitter interactions between the top container liners and the public. Adopting the 2030 Agenda and Sustainable Development Goals (SDGs) as a normative framework, this study analyses the strategic fit of the sustainability communications by top shipping companies internally (i.e. consistency with core business) and externally (i.e. consistency with public expectation). A combined method of qualitative content analysis and quantitative statistic test is employed. Our findings suggest a trend of diversification in shipping companies' sustainability communications which gradually extend from SDGs related to the industry's core responsibilities to peripheral responsibilities. Contrarily, a trend of convergence in the public's response is observed where the public's attention is increasingly diverted from SDGs pertaining to the industry's peripheral responsibilities to the core ones. Based on the opposite trends, theoretical and managerial implications for maritime scholars and industry players are discussed; Sustainable communication strategies for the shipping industry are highlighted.

Deploying, scheduling, and sequencing heterogeneous vessels in a liner container shipping route

Previous studies on liner container shipping operations usually assume identical container ships deployed in the same shipping route. However, in real operations, this assumption does not always hold considering the distinct capacities, ages, fuel efficiencies, cost structures, etc. of these ships. These distinctions significantly influence the number of containers transported, the bunker fuel consumption, and the operating cost of a shipping route. In this regard, this paper considers the joint ship deployment, sequencing, and scheduling problem for a fleet of heterogeneous vessels in a shipping route. A mixed integer programming model is developed to select the optimal ships from a set of candidate ships together with their sequences, schedules, and sailing speeds in the shipping route to minimize the total cost. A tailored solution algorithm is subsequently developed to calculate the global optimal solution. Numerical experiments demonstrate that this algorithm significantly outperforms the classical branch-and-cut algorithm in solving the model. In addition, by applying our model in a real-case shipping route, we find that the model is able to reduce the total cost by 5% compared with that considering homogeneous vessels. Finally, several managerial insights are obtained to guide the operations of a liner shipping route.

Probabilistic tabu search algorithm for container liner shipping problem with speed optimisation

This paper considers a container liner shipping problem with speed optimisation (CLSP-SO) to minimise the total costs of the fleet, which includes operating costs, capital costs and voyage costs. A mixed-integer nonlinear programming model is first formulated to illustrate the problem, in which the oil consumption of ships is treated as a cubic function of speeds. Then, the computational complexity of the problem is analysed and a lower bound is given based on the theoretical optimised speed of ships. To solve the problem, a probabilistic tabu search (PTS)-based algorithm is developed considering the NP-hardness of the problem. Extensive computational experiments on randomly generated data and a real-world case are conducted and the performance of the proposed method is compared with the lower bound and that of the basic tabu search (TS) algorithm. The results show that the proposed PTS-based algorithm obtains satisfactory solutions with respect to lower bounds in reasonable computation time and it outperforms the basic TS-based algorithm.

Sustainable competitiveness evaluation of container liners based on granular computing and social network group decision making

In the shipping industry, the sustainability of the shipping companies has received more attention besides the economic benefits. A suitable evaluation model can provide a credible sustainable improvement test and guide the operation and management of shipping companies. This study is concerned with a granular evaluation model for the sustainable competitiveness evaluation of container liners, where the interval linguistic version of the analytic hierarchy process is designed for comparing alternatives comprehensively. To obtain ideal consistent preference relations, we propose a modification method by constructing information granules and using particle swarm optimization. Moreover, based on the combination of individual preference relations and experts’ weights obtained from the social network, the aggregated overall opinion of alternatives is achieved. Furthermore, a case study evaluating the sustainable competitiveness of container liners is conducted to support the proposed evaluation framework’s feasibility and practicality.

Optimizing freight rate of spot market containers with uncertainties in shipping demand and available ship capacity

Liner container shipping company satisfies container shipping demand from both long-term contracts and spot market. Different from the shipping demand from long-term contracts whose freight rate is usually negotiated between the shipping company and the customer, the freight rate of the spot demand is usually determined by the shipping company itself. This paper thus focuses on how to determine the optimal freight rate of spot containers for each origin and destination (OD) pairs of a shipping network to maximize the total profit. To further reflect industry practice, two types of uncertainties are considered, i.e., the uncertain spot demand volume due to stochastic slot booking arrivals and cancelations, and the uncertain remaining ship capacity for the spot demand after satisfying other demand types with higher priority (e.g. delayed containers). This problem is first formulated as a two-stage stochastic nonlinear and nonconvex programming model. A tailored spatial branch-and-bound-and-Benders algorithm is then developed to obtain the global optimal solution of the model. Numerical experiments also demonstrate the efficiency of the solution algorithm and the applicability of the proposed model in improving the profit from the spot shipping demand.

Optimal Global Liner Service Procurement by Utilizing Liner Service Schedules

For global shippers (i.e., multinational manufacturers or retailers), strategic sourcing of container liner shipping services from ocean carriers is an important element of successful global supply chain management. We study how to utilize information about different ocean carriers’ liner service schedules so that shippers can optimize their sourcing decisions over the selection of carriers to transport container cargoes around the world through multiple shipping lanes. We first introduce a deterministic optimization problem, where cargo demands are given in advance and in which inventory holding costs are included to capture the impacts of liner service schedules on the total operating cost. We formulate the deterministic optimization problem as a mixed integer linear program, which can be simplified by exploiting a totally unimodular property, and can thus be solved directly by a general optimization solver. To further capture the impact of liner service schedules on shippers’ resilience to the uncertainties in cargo demands, we then introduce a two‐stage robust optimization counterpart of the deterministic problem based on a probability‐free demand uncertainty set. As the two‐stage robust optimization problem is challenging to solve, we derive some novel reformulations that can enable us to develop an effective solution method. By exploiting the information about liner service schedules, we show how our proposed models and solution method can help shippers to optimize their liner service procurement decisions.

Flexible Optimization of International Shipping Routes considering Carbon Emission Cost

Carbon emissions cost is a potential effective measure to restrict hydrocarbon pollution in the international shipping trade. The minimization of the total cost is pursued by ship operators, whereas voyage cost is increasingly involving the replacement of clean fuel and changing the cost of the shipping route. A flexible optimization method focusing on maximizing the total profit is developed in terms of sailing speed optimization and single port skips integrate carbon emission influence. An actual ocean shipping route from Shanghai to Rotterdam is applied to validate the effectiveness of the proposed models. The results have shown that the shipping route profit is volatile along with the sailing speed and the number of port calls. However, the profit will be maximized when applying the single port skip and will slow down the sailing speed at the same time. The demand of planned skip port can be supported by a short line container. A system composed of ocean container liner and short line container can improve the profit by 4.05% and reduce the carbon emission by 19.70%. Furthermore, sensitive results show that the profit is less affected by the changing of the carbon emission cost. A small size container has enough ability to solve the short transportation demand in adjacent ports and convert extraberthing cost into profit. These findings can provide reliable support for the shipping route decision process considering future carbon emission costs.

Container slot allocation and dynamic pricing considering overbooking and market segmentation

In this paper, we study the problem of slot allocation and dynamic pricing for container liner with uncertain demand. We consider the carrier’s overbooking strategy and market segmentation. A two-stage mathematical model is proposed for container liner slot allocation and dynamic pricing. After linearizing the model, CPLEX can be used to solve it. The results of numerical experiments show that the model considering both overbooking and market segmentation can significantly improve the revenue of container liner companies.

Support of the speed decision in liner operation by evaluating the trade-off between bunker fuel consumption and reliability

In liner container shipping, the optimization of bunker fuel costs and reliability can theoretically be achieved by steaming the distance in the available time at average, constant speed. However, in reality bunker fuel costs and reliability are mutually contradictory objectives. Due to incidents (e.g. technical problems on board of vessels, bad weather conditions, piracy) speed ups are necessary to arrive on schedule or at least to mitigate the delay. In this paper, a new approach to liner speed management is proposed. In order to manage the trade-off between bunker fuel consumption and reliability of services, a preventive buffer structure is built up to secure the schedule against delays. However, any analytical calculation of the structure and its effects can only be achieved with disproportionate effort. Therefore, a “discrete event simulation” is applied. Although a heuristic attempt does not provide the exact solution, reasonable and wide-ranged solutions are offered. Different decision alternatives are outlined, structured and tested to find appropriate speed profiles. For the evaluation of speed profiles three measures of reliability and deviation (α-reliability: ratio of punctual vessels [in%], β-deviation: average positive deviation from the schedule [in hours], γ-deviation: average negative deviation [in hours]) and costs are illuminated.

Influence of a cargo plan on the container ship port turnaround time

Nowadays, with patented technologies for the production of goods, the possibility of reducing their cost in order to maintain a competitive position in the commodity markets is supported by the rational organization of transportation. Thus, the transport component in the final cost of transported goods is reduced. At the same time, when using the same handling, lifting and transporting equipment from a limited number of global manufacturers, the possibility of reducing the cost of transport operations (both shipping and handling, including loading/unloading) depends only on their rational use. One of the mechanisms for rationalizing the loading and unloading operations carried out by container terminals is the rationalization of cargo plans of the serviced container ships. The versatility of their development is determined, first of all, by high requirements for the safety of navigation, which determine the provision of the necessary stability, unsinkability, the absence of a heel and difference that interfere with the work, the required sitting of the ship in the water, etc. On the other hand, the rational placement of containers in the slots and on the hatches covers of the container ships, corresponding to the voyage rotation (the sequence of visiting terminals on the trip in progress), provides an increase in the share of productive movements of handling, lifting and transporting equipment, reduces the required time for a ship to be under loading and unloading operations, which reduces the time of a group of ship trips on a string. Such calculations are complicated by the fact that the handling equipment used during the loading and unloading operations on a separate ship operates conditionally autonomously, each unit - for its own section of the ship (“bay”). Thus, the task can be solved only in a complex manner, coupled with the task of cranes allocation over the berth. The paper studies the issues of cargo planning of liner container ships from the standpoint of reducing the time of ship’s turnaround time due to rational assignment and use of port handling equipment.

An Attention Mechanism Oriented Hybrid CNN-RNN Deep Learning Architecture of Container Terminal Liner Handling Conditions Prediction.

The booming computational thinking and deep learning make it possible to construct agile, efficient, and robust deep learning-driven decision-making support engine for the operation of container terminal handling systems (CTHSs). Within the conceptual framework of computational logistics, an attention mechanism oriented hybrid convolutional neural network and recurrent neural network deep learning architecture (AMO-HCR-DLA) is proposed technically to predict the container terminal liner handling conditions that mainly include liner handling time (LHT) and total working time of quay crane farm (TWT-QCF) for a calling liner. Consequently, the container terminal oriented logistics generalized computation (CTO-LGC) automation and intelligence are established tentatively by AMO-HCR-DLA. A typical regional container terminal hub of China is selected to design, implement, execute, and evaluate the AMO-HCR-DLA with the actual production data. In the case of severe vibration of LHT and TWT-QCF, while forecasting the handling conditions of 210 ships based on the CTO-LGC running log of four years, the forecasting error of LHT within one hour is more than 97% and that of TWT-QCF within six hours accounts for 89.405%. When predicting the operating conditions of 300 liners by the log of five years, the forecasting deviation of LHT within one hour is more than striking 99% and that of TWT-QCF within six hours reaches up to 94.010% as well. All are far superior to the predicting outcomes by the classical algorithms of machine learning and deep learning. Hence, the AMO-HCR-DLA shows excellent performance for the prediction of CTHS with the low and stable computational consuming. It also demonstrates the feasibility, credibility, and realizability of the computing architecture and design paradigm of AMO-HCR-DLA preliminarily.

원전 격납건물 내 공극 검출을 위한 비파괴평가 기법 연구

원전 격납건물 내 공극 검출을 위한 비파괴평가 기법 연구

Container liner shipping network design with shipper’s dual preference

This paper addresses the container liner shipping network design by explicitly taking into account shipper's inertia preference and non-inertial preference. Firstly, using the double-constrained gravity model and Newton calibration method to predict the future OD demand matrix which is considered as the input of the model, and then the liner shipping company profit maximization is taken as the objective function to optimize the ship shipping routes, ship type and ship speed. A hybrid genetic algorithm is designed to solve CLSNDP (Container Liner Shipping Network Design Problem). We validate the proposed model by employing a real liner shipping network on the trade shipping route between Asia and West Europe. Through sensitivity analysis, it is found that the service level and market share of container liner shipping company can be improved by considering the dual preference of shippers. In the non-inertia preference of shippers, when cost preference of shippers is greater than time preference, using large ships (over 7000TEU) can achieve greater profits and realize the scale economies of lager ships.

On Probability Distributions of the Time Deviation Law of Container Liner Ships Under Interference Uncertainty

AbstractContainer liner shipping is a kind of transportation mode that is operated according to a schedule. Although the goal is to operate container liner ships on time, the actual arrival time and handling time often deviate from the schedule due to uncertain factors. The identification of a proper probability distribution to describe time deviation law will have a significant impact on accurately recognizing the uncertainty of the operation of container liner ships. In view of this problem, this paper discusses the basic characteristics of container liner ships’ operation time, analyses the properties of relevant probability distributions, and selects representative container ports around the world to collect data on the container liner ships’ operation time for statistical verification. The results show that under schedule constraints and interference uncertainty, the time deviation presents a specific state between a fixed length and random distribution that conforms to the properties of an Erlang distribution. Given that container liner shipping follows the same operation rules worldwide, it is reasonable to deduce that the time deviation law could be generalized to other container ports. Finally, the practical value of this study is demonstrated through quantitative evaluation of port congestion degree under various probabilistic models.

Research on feeder network design: a case study of feeder service for the port of Kotka

By exemplifying the feeder service for the port of Kotka, this study proposed a multi-objective optimization model for feeder network design. Innovative for difference from the single-objective evaluation system, the objective of feeder network design was proposed to include single allocation cost, intra-Europe cargo revenue, equipment balance, sailing cycle, allocation utilization, service route competitiveness, and stability. A three-stage control system was presented, and numerical experiment based on container liner’s real life data was conducted to verify the mathematical model and the control system. The numerical experiment revealed that the three-stage control system is effective and practical, and the research ideas had been applicable with satisfactory effect.

Joint Optimization of Ship Sailing Speed and Container Handling Rate for a Near-sea Liner Service Route

This paper jointly designs the optimal ship sailing speeds on shipping legs and the optimal handling rates at ports of a near-sea liner service route operated by a container liner shipping company. A mixed integer linear programming model is developed, which can be solved directly by the commercial solvers to give a global optimal solution. The model is further applied to a real-life case. Results demonstrate that both bunker price and unit inventory cost affect the optimal ship sailing speed and the optimal container handling rate.

Coopetition in the supply chain between container liners and freight forwarders: a game theory approach

ABSTRACT A common objective of container liners is to expand to both ends of the supply chain, thereby providing customers seamless access to a wider range of logistics. There are many overlaps between the service provided by container liners and freight forwarders, which may affect their relationships. However, there is a lack of research on this issue. This study attempts to analyze the basis for cooperation, the causes of conflict, and the means to achieve sustainable relationships in the supply chain. It is based on container liners’ strategy to extend end-to-end service and improve layout through acquisition and investment. The study fills the gap in the current literature on the relationship between container liners and freight forwarders. It is also one of the few studies to apply game theory to coopetition in the shipping industry. The results have practical significance in terms of learning how to improve cooperation in the supply chain.