Container Terminal Operations Research Articles

Technical Efficiency of Container Terminal Operations in Southwestern Seaport in Nigeria

Containerization plays a crucial role in international trade. It promotes the oceanic business, generally pertinent to container terminals. Despite the various benefits of the container terminal to maritime trade and the economic development of nations with seaports, Nigerian ports are suffering from a progressive decline compared to other thriving ports in other parts of the globe. Hence, this study evaluates the technical efficiency of container terminal operations in southwestern seaport in Nigeria. Survey research design was adopted for this study in which Multi-stage sampling technique was used. Both primary and secondary data were collected from the annual report and questionnaire respectively from staff of the container terminal operators in Tincan Island Port Complex and Apapa Port Complex. The result from the findings showed that four factors influenced container terminal capacity and port performance. These include port charges, stevedoring operations, unserviceable cranes and ship calls. Also, the Data Envelopment Analysis (DEA) findings showed that AP Moller Terminal, PCHS, and PTML have a crste, vrste, and scale efficiency of 1, indicating they are fully technically efficient under both constant and variable returns to scale. It was concluded that AP Moller Terminal, PCHS and PTML are the most efficient terminal in South-Western Ports in Nigeria. It was recommended that periodic training and retraining of staff handling modern equipment should be prioritized and also, increase in port charges by the terminal operators should be addressed to encourage freight forwarders to clear their cargo on time at the port.

Assessment of Container Terminal Operations in South-Western Ports in Nigeria

Containers, a global maritime trade influencer, have increased the importance of ports. Ports serve as an economic catalyst for revenue and employment. The importance of container transport cannot be overemphasized in international trade especially in Nigeria. Hence, it becomes expedients to assess the elements of container terminal capacity, analyse the trend of cargo throughput and as well determine the relationship between handling equipment and cargo dwell time in Western ports in Nigeria. The study adopts multistage sampling. Also, both primary and secondary data were collected from the staff of the container terminal operators in Tincan Island Port Complex and Apapa Port Complex and 347 respondents were chosen using Yamene formular. Furthermore, Descriptive statistics such as frequency table, line graph, bar charts were used to examine the elements of container terminal capacity, analyse the trend of cargo throughput. The inferential statistics such as regression analysis was used examines the relationship between thandling equipment and cargo dwell time. The result showed a decline in cargo throughput from 2019 to 2020, a trend that can be directly attributed to the COVID-19 pandemic. Also, it was shown that the coefficient of handling equipment is 0.725, indicating that for every unit increase in the handling equipment score, the cargo dwell time increases by 0.725 units. The t-value of 21.558 and a significance level of 0.000 signify that the handling equipment is a significant predictor of cargo dwell time. Based on the findings of the study, it was concluded that terminal space, handling equipment, daily stock and port labour were significant factors or elements of container terminal capacity. It was recommended that Nigerian Ports Authority should invest more on sustainable infrastructure and terminal operators and stevedoring company should train and retrain their staff on modern handling equipment.

Robust multi-equipment scheduling for U-shaped container terminals concerning double-cycling mode and uncertain operation time with cascade effects

The integrated scheduling of quay cranes, internal vehicles, and yard cranes in container terminals aims to improve port operations and often requires scheduling robustness under uncertainty with cascade effects. In container terminal operations, uncertainty in equipment operating time poses challenges to effective scheduling, as even small fluctuations can create cascade effects throughout the operations, rendering the original schedule ineffective. This research aims to develop a new method that enables a balance between optimization and robustness in container terminal scheduling. Additionally, the double-cycling operation mode and U-shaped port layout, known for their improved efficiency in container terminals, are gaining increasing attention and hence are incorporated into this study. It creates a three-stage hybrid flow shop scheduling problem with bi-directional flows, waiting time, and uncertain operation time. To address the complex problem, a mixed integer programming model is proposed to characterize the integrated scheduling problem, and an index based on complex network structure entropy is designed to evaluate the anti-cascade effect as well as the robustness of the schedule. The index and makespan serve as the bi-objectives, transforming the original problem into a bi-objective optimization one. The non-dominated sorting genetic algorithm-Ⅱ with appropriate coding and decoding rules is utilized to solve the model and obtain a set of Pareto frontier solutions. The feasibility of the new method is verified through a real case analysis. Specifically, comparative analysis with basic stochastic programming, basic robust optimization, triangular fuzzy programming, and maximum gap method are used to demonstrate the effectiveness of the new method. The paper also provides insightful practical implications for port managers, and the genericity of the method could also contribute to its practical values spreading to a wider scope of beneficiaries, such as manufacturing warehousing and distribution management.

Multiple Container Terminal Berth Allocation and Joint Operation Based on Dueling Double Deep Q-Network

In response to the evolving challenges of the integration and combination of multiple container terminal operations under berth water depth constraints, the multi-terminal dynamic and continuous berth allocation problem emerges as a critical issue. Based on computational logistics, the MDC-BAP is formulated to be a unique variant of the classical resource-constrained project scheduling problem, and modeled as a mixed-integer programming model. The modeling objective is to minimize the total dwelling time of linerships in ports. To address this, a Dueling Double DQN-based reinforcement learning algorithm is designed for the multi-terminal dynamic and continuous berth allocation problem A series of computational experiments are executed to validate the algorithm’s effectiveness and its aptitude for multiple terminal joint operation. Specifically, the Dueling Double DQN algorithm boosts the average solution quality by nearly 3.7%, compared to the classical algorithm such as Proximal Policy Optimization, Deep Q Net and Dueling Deep Q Net also have better results in terms of solution quality when benchmarked against the commercial solver CPLEX. Moreover, the performance advantage escalates as the number of ships increases. In addition, the approach enhances the service level at the terminals and slashes operation costs. On the whole, the Dueling Double DQN algorithm shows marked superiority in tackling complicated and large-scale scheduling problems, and provides an efficient, practical solution to MDC-BAP for port operators.

Operational efficiency for container terminal operators with undesirable outputs: slacks-based measures

ABSTRACT Operational efficiency is crucial in the container terminal industry to reduce costs, increase throughput, enhance customer satisfaction, optimize the supply chain, improve safety, minimize environmental impact, and ensure adaptability and resilience in a dynamic and competitive market. The article aims to estimate operational efficiency for CTOs by the Slacks-Based Measures (SBM) model when considering CO2 emissions and work accidents as undesirable outputs. In doing so, this paper adopted the cluster analysis to select homogeneous CTOs acting as Decision-making Units (DMUs). CTOs in the Cai Mep-Thi Vai port (the CMTV case) were then empirically studied to verify the validity of the suggested model. The results could have real-world applications for CTOs looking for managerial actions to boost operational efficiency and maintain high-quality growth. Additionally, the research model may provide an analytical reference for relevant port management applications. In particular, this study offers CTOs a scientific framework for evaluating the operational efficiency of CTOs located in a port.

Optimization for Green Container Shipping: A Review and Future Research Directions

Maritime freight transportation is one of the least emissions-producing transportation alternatives in terms of transported tonnage per distance. However, it produces a high amount of emissions as around 80% of international freight transportation is conducted through seas and 20% of maritime transportation is conducted through container shipping. This makes it crucial to reduce emissions in container shipping. In this regard, this study reviewed previous studies on the environmental optimization of container shipping and identified various future research directions. The results showed that in the sea segment of environmental optimization of container shipping, decisions which require further attention include resource allocation, emission reduction technology choice, disruption recovery, freight rate optimization, and shipment scheduling. The decisions that require future research in the port segment are related to internal transportation and handing operations in container terminals (i.e., yard crane deployment, yard truck deployment, yard truck scheduling, yard container stack allocation, yard container retrieval), renewable energy source installation, and emission reduction technology choice. Vessel scheduling and speed optimization decisions are the most frequently studied decisions in the sea segment, but they are rarely considered for inland shipping of containers. In the sea-port combined segment of container shipping, future studies are required in quay crane scheduling, vessel scheduling, container route allocation, ship route allocation vessel deployment, and emission reduction technology choice. The least studied decision in the door-to-door segment of container shipping includes hub location-allocation, empty container relocation, ship route allocation, vessel deployment, environmental taxation and subsidy scheme, emissions reduction technology choice, and speed optimization. It was also demonstrated that modeling of future studies should more frequently consider uncertainties and social sustainability parameters.

Efficient Container Logistics System Model

The containers were associated with import-export businesses via sea transport. It had an impact on economic value and was essential for logistics development. The Overseas Container Management System literature review found numerous papers that tend upward in port operations, container yards, or container terminals. This study follows this trend and is driven to learn about processes and container management systems in container yards. The research aims to study container management system analysis and the factors influencing an efficient container yard management system. This research is applied research, which includes collecting relevant documents, actual field data, surveys, and observation techniques. The sampling frame consisted of 400 trucks in a specific case study of an empty container terminal operation area in Bangkok port (Cargo Operations Division 3). Data was collected by the Case Record/Report Form (CRF). Binary logistic regression was used to analyze the relationship between the independent factors and the dependent variable. Keywords: Container, Empty Container Terminal, Container Yard, Container Management System

Global terminal operators: a competitive strategic position analysis

ABSTRACT Port operators and liner shipping companies attempt to gain cost and competitive advantages by providing services in complementary maritime-related areas. In line with this purpose, companies undertake a task known as Global Terminal Operator (GTO). Substantially, there are more than 21 GTOs of various sizes involved in container terminal operations worldwide, handling 80% of the total containerized cargo traffic. In recent years, there have been drastic changes in the GTO market with numerous mergers, acquisitions, and concessions. However, academic and sectoral studies have fallen short of keeping up with these changes. To fill the gap in research, a dynamic portfolio analysis has been carried out within the scope of this novel study for the first time for the GTOs with the help of BCG Matrix analyses. Findings reveal that GTOs followed different development paths with respect to their distinctive characteristics. Major operators maintained their market dominance, unlike the minors who followed an unsteady path of development. This paper contributes to the academic literature by conducting a comprehensive market analysis for the GTO sector and revealing the dynamic development courses as well as strategic competitive positions of the operators from a managerial perspective toward shaping future strategic plans of the industry stakeholders.

Two-Stage Robust Programming Modeling for Continuous Berth Allocation with Uncertain Vessel Arrival Time

In order to mitigate the environmental pollution caused by sea freight, we focused on optimizing carbon emissions in container terminal operations. This paper establishes a mixed integer programming (MIP) model for a continuous berth allocation problem (CBAP) considering the tide time window. We aimed to minimize the total carbon emissions caused by the waiting time, consumption time and deviation to berth preference. In order to overcome the influence of an uncertain arrival time, the proposed MIP model was extended to mixed integer robust programming (MIRP) models, which applied a two-stage robust optimization (TSRO) approach to the optimal solution. We introduced an uncertainty set and scenarios to describe the uncertain arrival time. Due to the complexity of the resulting models, we proposed three particle swarm optimization (PSO) algorithms and made two novelties. The numerical experiment revealed that the robust models yielded a smaller variation in the objective function values, and the improved algorithms demonstrated a shorter solution time in solving the optimization problem. The results show the robustness of the constructed models and the efficiency of the proposed algorithms.

Berth allocation and scheduling at marine container terminals: A state-of-the-art review of solution approaches and relevant scheduling attributes

AbstractMarine container terminals play a significant role for international trade networks and global market. To cope with the rapid and steady growth of the seaborne trade market, marine container terminal operators must address the operational challenges with appropriate analytical methods to meet the needs of the market. The berth allocation and scheduling problem is one of the important decisions faced by operators during operations planning. The optimization of a berth schedule is strongly associated with the allocation of spatial and temporal resources. An optimal and robust berth schedule remarkably improves the productivity and competitiveness of a seaport. A significant number of berth allocation and scheduling studies have been conducted over the last years. Thus, there is an existing need for a comprehensive and critical literature survey to analyze the state-of-the-art research progress, developing tendencies, current shortcomings, and potential future research directions. Therefore, this study thoroughly selected scientific manuscripts dedicated to the berth allocation and scheduling problem. The identified studies were categorized based on spatial attributes, including discrete, continuous, and hybrid berth allocation and scheduling problems. A detailed review was performed for the identified study categories. A representative mathematical formulation for each category was presented along with a detailed summary of various considerations and characteristics of every study. A specific emphasis was given to the solution methods adopted. The current research shortcomings and important research needs were outlined based on the review of the state-of-the-art. This study was conducted with the expectation of assisting the scientific community and relevant stakeholders with berth allocation and scheduling.

Blockchain adoption in container shipping: An empirical study on barriers, approaches, and recommendations

Blockchain is an emerging technology in logistics and supply chain management. However, its adoption is still in a doldrum with limited success. This study explores container shipping service providers’ (CSSPs) current adoption status and perceived barriers in integrating blockchain applications before providing adoption recommendations. A qualitative analysis was conducted on thirty-two interviews with experts holding managing positions from container terminal operators, shipping companies, and freight forwarders. Thematic analysis was employed to extract and aggregate information from the qualitative database. This study revealed the difference between CSSPs’ perceptions of blockchain adoption barriers and, accordingly, their adopting approaches. A challenging implementing process for the current blockchain applications in container shipping was depicted with ten barriers and twenty-nine connections. Industry experts provided six recommendations for successful blockchain adoption to address the complicated situation. This paper deepens the knowledge about blockchain in supply chains, especially maritime logistics operations. It sheds light on the complexity of perceived adoption barriers, their effect on CSSPs’ approaches to blockchain applications, and potential digitalization policies to be taken.

Model for Evaluating the Effectiveness of Cargo Operation Strategy in an Inland Container Terminal

The paper discusses the issue of unproductivity during the implementation of operations in inland container terminals. The authors hypothesize that the two main factors influencing the number of unproductive manipulations are the adopted operating strategy and the occupancy level of the storage yard. The presented model classifies the operation time and the waiting time for container handling separately, and also compares the impact of the terminal storage occupancy and selected strategies on the handling time. Based on the collected data, the impact of the number of occupied storage places and the frequency of repetition of operations on the average time of handling a freight unit are simulated. It is noticed that increasing the occupancy of the terminal area above 35% results in a significant increase in the frequency of repetition of operations. In the case of terminal area occupancy of about 50%, the average waiting time for service and the service of a freight unit itself may vary significantly, depending on the adopted strategies for the implementation of operations.

Technical efficiency evaluation and ranking of container terminal operators through DEA

In today’s competitive business environment the evaluation and ranking of container terminals plays a crucial role. Data Envelopment Analysis (DEA) models are suitable to measure the efficiencies of alternatives specified with multiple inputs with multiple outputs, where as Stochastic Frontier Analysis (SFA) models are suitable to measure the efficiencies of alternatives specified by multiple inputs with single output. In this four inputs and four outputs are considered for the evaluation of technical efficiency of container terminals and DEA is implemented to evaluate the performance of these container terminals based on technical efficiency. Also Regression analysis is performed to identify the factors which affect the technical efficiency mostly.

The Integrated Scheduling Optimization for Container Handling by Using Driverless Electric Truck in Automated Container Terminal

With the increasing maturity of automatic driving technology, the commercial value of driverless container trucks has been gradually excavated. Compared with social roads, the internal roads in the port area have certain practicing advantages. By taking into account the operational characteristics of the driverless electric container truck and the coordination of quay and yard cranes, this paper aims to explore the configuration and optimized scheduling model of the driverless electric container truck with the objective of minimizing overall energy consumption. The results show that the optimized allocation and scheduling of driverless electric trucks can minimize the total energy consumption of terminal operation without delaying the shipping schedule, and has obvious advantages over traditional manual driving diesel trucks and Automated Guided Vehicles in terms of operation efficiency, economy, and sociality. The results can also provide certain decision-making reference for the selection of horizontal transportation equipment and collaborative scheduling of multi-type loading and unloading equipment resources of container terminal operators.

A bibliometric analysis and assessment of container terminal operations research

PurposeThe paper undertakes a bibliometric analysis and assessment of journal publications in the field of container terminal operations research (CTOR), in an attempt to identify high-impact papers (HIPs) published in Science Citation Index/Social Science Citation Index (SCI/SSCI) journals of CTOR subject category from 1973 to 2020.Design/methodology/approachA structured approach for identifying the HIPs is developed based on the utilization of bibliometric and network analyses.FindingsThe CTOR papers are assessed in terms of publication outputs, distribution of outputs in SCI/SSCI journals, authorship, institutions and countries, as well as citation life cycles of papers with the highest total citations since their publication until the year 2020. The results show that between 1989 and 2015, there were 82 HIPs in the field of CTOR, which have been cited at least 200 times, with more than 50% of these citations allocated in the second part of paper citation life cycle according to the database of Google Scholar.Practical implicationsThe practical implication of the aforementioned reviewing and assessing journal publications of CTOR is that it offers the ability to reveal the tone of its development through addressing main characteristics of the relevant HIPs as determined by the highly cited papers in this field of research.Originality/valueThis paper offers a unique analysis and assessment in the field of CTOR by identifying the relevant HIPs and their associated scientific actors (authors, institutions and countries), thus facilitating the future research effort in the field of CTOR.

Design and development of in‐the‐loop test and evaluation platform for space allocation at shipping container terminal

AbstractAs a vital component in the shipping industry, coastal container terminals must be developed in a sustainable manner. The container receiving process is a crucial aspect of container loading and transportation and is the cornerstone of container terminal operations. This process is characterized by its discrete random events. To model this process, the testbed was designed and developed using a Hierarchical Generalized Stochastic Petri Net (HGSPN) workflow engine to drive the data and simulate the container receiving process through the interplay of resources and changes. Random indexing was utilized to mimic the discrete randomness of the operations. The performance of the container receiving process was validated and evaluated through the construction of an operational energy and efficiency‐focused container receiving evaluation model. Results showed that the intelligent container receiving system, tested on the in‐loop platform, can effectively evaluate the strengths and weaknesses of container receiving, leading to continuous improvement of the system and demonstrating its significant practical value.

Inbound container storage pricing considering price-dependent container storage time and congestion in container terminals

ABSTRACT Congestion at ports and railheads is attracting more and more attention from both the government and industry. In this paper, we intend to improve container terminal operation efficiency from the perspective of inbound container storage pricing. We study a two-stage pricing game model for a profit-maximising shipping company and a container terminal operator. Two types of objective functions are investigated for the container terminal operator: profit maximisation and cost minimisation. Price-dependent container storage time is considered. After theoretical analysis, the pricing equilibria is derived. Through numerical studies, we find that the cost-minimising objective is recommended for the terminal operator to relieve the stress of yard congestion. Container terminal operators have an incentive to raise storage prices to cope with congestion in terminal yards.

Optimizing container terminal operations: a systematic review of operations research applications

Optimizing container terminal operations: a systematic review of operations research applications

Noise pollution of container handling: External and abatement costs and environmental efficiency

While previous studies have pointed to their economic significance, terminal operations are frequently ignored in transport appraisal and policy analysis. This paper develops a generic model framework for estimating noise emissions from container terminal operations to derive key metrics for port policy analysis. A novel microeconomic production model that accommodates basic acoustics is proposed. Based thereon, abatement costs are derived using optimization and marginal external costs and efficiency scores are estimated using panel data frontier estimation. The virtues of the modeling approach are illustrated using noise meter readouts combined with port activity and meteorological data from the port of Oslo, Norway.

Solution for the Problem of Sustainable Staff Scheduling in Semi-Automated Dock Container Terminals in Ports

Port operations in container terminals are as important as container transportation itself. A port has a complex system in which a wide variety of operations take place, and a wide variety of resources are required to interact with each other. The aim of a port operator is to complete the service required in the shortest time and in the most efficient way. The quayside of the port, the equipment used such as cranes and field vehicles, and the operations officer and personnel are factors that directly affect the service provided at a port. The port management aims to maximize efficiency by reaching the maximum number of movements with the least possible cost. Increasing the efficiency and quality of the working personnel is extremely important in achieving this aim. This study provides efficient, fair, and balanced scheduling of field personnel and shift supervisors working in port operations using a real-life case of the semi-automated docks at an international port. A goal-programing model is constructed to manage the workforce needed by the port for a one-week working period and to assign the shift supervisors to the shifts in a balanced way. The personnel’s preferences and qualifications, which directly affect productivity, are also considered while planning. Results show an increase in productivity, quality of life, concentration, and employee job satisfaction. The results of the suggested mathematical model in the study show that the demands of the workers facing conflicting constraints were met with the least deviation from goals.