Container Terminals Research Articles

A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO2 Emissions Considerations in Container Terminals

Background: In container terminals, optimizing the scheduling of external trucks and yard cranes is crucial as it directly impacts the truck turnaround time, which is one of the most critical performance measures. Furthermore, proper scheduling of external trucks contributes to reducing CO2 emissions. Methods: This paper proposes a new approach based on a mixed integer programming model to schedule external trucks and yard cranes with the objective of minimizing CO2 emissions and reducing truck turnaround time, the gap between trucking companies’ preferred arrival time and appointed time, and the energy consumption of yard cranes. The proposed approach combines data analysis and operations research techniques. Specifically, it employs a K-means clustering algorithm to reduce the number of necessary truck trips for container handling. Additionally, a two-stage mathematical model is applied. The first stage employs a bi-objective mathematical model to plan the arrival of external trucks at the terminal gates. The second stage involves a mathematical model that schedules yard cranes’ movements between different yard blocks. Results: The results show that implementing this methodology in a hypothetical case study may lead to a substantial daily reduction of approximately 31% in CO2 emissions. Additionally, the results provide valuable insights into the trade-off between satisfying the trucking companies’ preferred arrival time and the total turnaround time. Conclusions: The integration of data clustering with mathematical modeling demonstrates a notable reduction in emissions, underscoring the viability of this strategy in promoting sustainability in port-related activities.

Strategies for Reducing Demurrage at the Douala Container Terminals (RTC Terminal) during Importation

COVID-19 diverse methods and procedures of different port actors are some of the reasons for increasing demurrage for containerized goods. Demurrage is the additional charges levied by the maritime carrier on the users of its equipment (container) after the container passes the normal time in the seaport, which is 11 days in Cameroon (Douala). This study aims to investigate the main causes of increasing demurrage at the Douala container terminal and recommend strategies to reduce the increasing demurrage at the port RTC terminal (Container terminal management or Regie du Terminal a Conteneurs). This study uses a target population of 700 actors selected using a stratified random techniques in different fields linked to the international logistics chain and the Douala port in particular. Moreover a total of 490 participants responded to the questionnaire distributed to them. Descriptive statistics such as table and pie chart were used to analyze the data collected during the research. Findings demonstrated that the activities of the different actors involved in the logistics chain, namely the customs administrators, customs brokers, importers, shipping line exporters, PAD (Douala Autonomous Port) and other actors such as Society General de Surveillance (SGS), Cameroon Customs Information System (CAMCIS) and RTC Terminal are the main causes of the increased demurrage at the Douala port. The study recommends, amongst others, eliminating public holidays and weekends by shipping line when counting the demurrage days at the Douala port. Also we recommend that, the demurrage days should only start when the manifest is visible to all the actors, which is not the case. Equally, the government should impose the demurrage charge on the actors, which are the principal cause of demurrage at the port. It should be noted that with the implementation of the above recommendations by the different actors, demurrage will reduce in the Douala port and many African countries.

Integrated Location Selection and Scheduling Problems for Inland Container Transportation

Well-organized network configuration is the key to the success of inland container transportation systems. In this study, we firstly propose an integrated framework for the location selection of inland container depots (ICDs) and the scheduling of containers and trucks. The objective is to minimize the total cost of setting up the ICDs and transportation cost associated with trucks and containers. A mixed-integer linear programming (MILP) model is developed to solve the proposed problem. The computational studies show that the proposed decision approach is effective and can reduce the total operating costs of ICDs and transportation costs of containers. Sensitivity analysis on the impact of customer distributions and the number of ICDs on the total cost are conducted to reveal the characteristics of the problem. The utilization of ICDs can significantly improve the efficiency of the transportation network, i.e., the total cost is reduced by at least 27% for the proposed instances, and the transportation distance of empty containers is reduced by at least 4%. Finally, managerial insights and future research directions are provided.

Flexible storage yard management in container terminals under uncertainty

As the port bottleneck shifts from the shore side to the yard side, yard management is crucial to the operation efficiency of the container port. This paper studies the yard management problem in container terminals under the flexible storage strategy which does not fix the size of the storage templates in the yard. The problem considers the uncertainty of container demand and the flexibility of the block and jointly optimizes the storage space allocation, yard crane deployment, and container allocation problems. A two-stage stochastic optimization model under uncertainty is established to minimize the port operation cost. Two heuristic algorithms, a column generation-based heuristic algorithm and a tabu search algorithm, are proposed to solve the model. Numerical experiments validate the effectiveness of the proposed algorithms. Furthermore, some management implications for port operators are proposed according to the results of sensitivity analysis experiments.

Unmanned surface vehicles (USVs) scheduling method by a bi-level mission planning and path control

To enhance the operational efficiency of container terminals, we propose a bi-level scheduling method that employs unmanned surface vehicles (USVs) to transport containers exclusively between different berths on the waterside of terminals. In the upper level, Considering time windows, berth coordination, energy replenishment, etc., we formulate the mission decision model to obtain a cost-effective USVs shipping solution by minimizing unplanned delay and total execution cost. In the lower level, considering path distance, path smoothness, and motion constraints, we develop the USV path control model to achieve the USV path planning and reduce path tracking errors. Finally, we integrate the advantages of the chaotic Electron Search and multi-population Genetic Algorithm (ES-mGA) to solve the bi-level USVs scheduling model. Experimental results demonstrate the effectiveness of our approach and algorithm in guiding the USVs to efficiently accomplish container transshipment and acquire stable USV sailing states.

A decomposition-based optimization method for integrated vehicle charging and operation scheduling in automated container terminals under fast charging technology

The increasing utilization of battery-powered automated guided vehicles in automated container terminals, has an important consequence on terminal cost and efficiency. How to tackle integrated vehicle charging and operation scheduling problem to maintain high terminal performance is prominent for sustainable port operation. In this paper, fast charging technology is investigated, and a mixed integer programming model for this complicated scheduling problem is constructed, which aims to reduce charging cost and penalty cost related to makespan, and includes sequence-related constraints, time-related constraints and energy-related constraints. A decomposition-iteration algorithm is proposed to solve this problem, and furthermore it is combined with a simulation-based optimization method to address practical-sized instances. Numerical experiments on real-world cases are conducted to verify the efficiency and effectiveness of the proposed solution algorithm. Insightful managerial implications are derived by comparative analysis on charging rules and charging facility locations, and sensitivity analysis on charging power, charging facility configuration and vehicle configuration. Experimental results provide valuable references for terminal managers to make configuration and scheduling decisions for battery-powered vehicle transporting systems.

Yard Space Allocation Algorithm for Unloading Containers at Marine Terminals

The issue of unloading efficiency for containers is the operational bottleneck for most traditional container terminals. In addressing the intricate challenges of space allocation in container yards during ship unloading, this study focuses on the real-time, dynamic decision-making needs that are currently unmet by existing planning methods. To tackle this, the article introduces a novel model for container space allocation that aims to maximize the “attractiveness” of yard spaces. This model factors in key considerations like the allocation of container handling equipment resources, the rate of container handling equipment traversing the yard, and container handling equipment operations across containers. A unique Monte Carlo tree search (MCTS)-based algorithm is developed to solve this multi-objective problem. The algorithm’s efficacy is rigorously tested via numerical experiments, where it outperforms existing approaches like UCT-MCTS, AMAF-MCTS, and manual scheduling plans using practical engineering examples. This research not only provides a more dynamic and efficient method for yard space allocation but also offers empirical evidence to support its practicality and effectiveness.

Battery-powered automated guided vehicles scheduling problem in automated container terminals for minimizing energy consumption

Battery-Powered Automated Guided Vehicles (B-AGVs) are important equipment used to transfer containers between the seaside and the landside in automated container terminals. Due to their limited battery capacity, the B-AGVs require battery recovery when their battery reaches the threshold. However, the processing capacity of electrical battery swapping stations is limited, it is crucial to avoid congestion in swapping station. Considering that the scheduling problem of B-AGV in the terminal is time intensive, this paper proposes a set partitioning method based on breadth-first and depth-first search to solve the established mixed integer programming model. Combined with the operational characteristics of the terminal, this paper adopts the flexible pooling strategy to effectively matches the inbound and outbound containers to form dual-cycle operation of B-AGVs, which can reduce the computational complexity and thus improving the solution efficiency. In addition, the record-to-record travel algorithm is applied to improve the quality of the solution. Finally, the effectiveness of the proposed model and solution method is evaluated through numerical experiments. Besides, the applicability of the flexible pooling strategy to different container terminals is studied, and the impact of the number of B-AGVs and the capacity of swapping stations on the energy consumption of B-AGVs is investigated, and some managerial insights are given accordingly.

The impact of contemporary socio-economic and technological factors on container terminal performance

PurposeThis present study uses political, economic, social, technological, legal and environmental (PESTLE) analysis and the strategic management theory to examine how external factors, namely the coronavirus (COVID-19) pandemic, the industrial revolution (IR) 4.0 technologies, the fuel price crisis and Sultanate of Oman Logistics Strategy (SOLS) 2040, affect the performance of container terminals in Oman.Design/methodology/approachA hybrid decision-making method that combined the analytical hierarchy process technique and Bayesian network model was used to achieve the objective of the present study.FindingsThe COVID-19 pandemic (54.60%) most significantly affected the performance of container terminals in Oman, followed by IR 4.0 technologies (19.66%), SOLS (17.00%) and fuel price crisis (8.74%). Container terminals in Oman were also found to perform “moderately,” considering the uncertainty of external factors.Research limitations/implicationsThis study enriches existing literature by using PESTLE analysis to assess the impact of the external business environment on firm performance in the context of the maritime industry as well as highlights how challenging external environmental factors affect the performance of container terminals in Oman.Originality/valueThis study contributes to developing novel study models and determining the performance level of container terminals in Oman considering integrated uncertainties and external factors such as the COVID-19 pandemic, IR 4.0 technologies, the SOLS 2040 and the fuel price crisis.

Research on the Multi-Equipment Cooperative Scheduling Method of Sea-Rail Automated Container Terminals under the Loading and Unloading Mode

A sea-rail automated container terminal (SRACT) plays a crucial role in the global logistics network, combining the benefits of sea and railway transportation. However, addressing the challenges of multi-equipment cooperative scheduling in terminal and railway operation areas is essential to ensure efficient container transportation. For the first time, this study addresses the cooperative scheduling challenges among railway gantry cranes, yard cranes, and automated guided vehicles (AGVs) under the loading and unloading mode in SRACTs, ensuring efficient container transportation. This requires the development of a practical scheduling model and algorithm. In this study, a mixed integer programming model was established for the first time to study the multi-equipment cooperative scheduling problem of a SRACT under the loading and unloading mode. A self-adaptive chaotic genetic algorithm was designed to solve the model, and the practicability and effectiveness of the model and algorithm were verified by simulation experiments. Furthermore, this study also proposes an AGV number adjustment strategy to accommodate changes in vessel arrival delays and train container types. Simulation experiments demonstrated that this strategy significantly reduces loading and unloading time, decreases equipment energy consumption, and improves the utilization rate of AGVs. This research provides valuable guidance for ongoing SRACT projects and advances and methodological approaches in multi-equipment co-operative scheduling for such terminals.

Analysis of the Key Factors Influencing Automation Transformation in Container Terminals Based on the Dempster–Shafer Evidence Interval Method

The steady growth of container volume and aggressive shipping alliances have intensified competition among terminals. With the rapid development and application of modern information and communication technology, automation is a great way to promote terminals’ sustainable development. The objectives of this study are to analyze the key factors influencing automation transformation and provide theoretical guidelines for implementing automation transformation. Based on the literature review, the main factors influencing the automation transformation of container terminals are characterized and analyzed. They are divided into four categories: technical feasibility, external promotion, self-constraints, and goals/demand. Thereafter, a novel multi-source data fusion method, the Dempster–Shafer evidence interval method (DSIM) based on Dempster–Shafer evidence theory and interval value, is proposed to fuse conflicting and uncertain opinions among experts. This method is effective for expert opinion elicitation. Using DSIM, the key factors’ relative importance and their relationship are examined based on the opinions of experts in China. The results show that technical feasibility is the most important factor category in the foundation of automation transformation. Finally, a generalized planning framework for constructing automation transformation schemes is established, providing references and suggestions for terminals’ decision-makers.

Spillover effects from inland waterway transport development: Spatial assessment of the Rhine-Alpine Corridor

Inland waterways have the potential to enhance port-hinterland connectivity and foster sustainable freight transport. Their development as transport corridors is highly dependent on geography, yet spatial spillovers of port throughput are often overlooked. In Europe, the configuration of inland container terminals can lead to cross-border spillovers. This paper analyzes inland container throughput between 2007 and 2021 in the Rhine-Alpine Corridor to quantify its spatial dependence and economic spillover effects. The assessment involves 43 regions from Belgium, France, Germany, Netherlands, Luxemburg, and Switzerland. A Spatial Durbin Model is developed accounting for economic conditions, fixed effects, and time trends. The results suggest that throughput exhibited spatial concentration patterns, which intensified after water levels dropped in 2018. Second, the spatial dependence is heterogeneous between transport performance in tonne-km vs. TEU-km. Third, technological resources and population density were positively associated with throughput, while the opposite was found for employment and motorways. Notably, the spillovers of technological resources and employment were considerably higher than the local impact. Based on these findings, the paper advises on spatially oriented policies to address low water levels, workforce decline, and the need for new business models.

The Role of Freight Forwarding Services in Supporting Export Activities in PT Citra Trans Buana Kargotama Jakarta

The purpose of this study was to obtain a deeper description and understanding of the role of Freight Forwarding in supporting export activities at PT Citra Trans Buana Kargotama Jakarta. This research was conducted using a qualitative descriptive method, which is a problem formulation that guides research to explore and describe what will be studied thoroughly, broadly, and deeply. and The data used in this study is primary data obtained through direct interviews with PT Citra Trans Buana Kargotama Jakarta. Based on the results of research on export activity procedures at PT Citra Trans Buana Kargotama Jakarta, namely from exporters sending Shipping Instructions to PT Citra Trans Buana Kargotama Jakarta and then to DHL Express (couriers). While the parties and agencies directly related to PT. Citra Trans Buana Kargotama Jakarta is an exporter, importer, agent of freight forwarder, customs, shipping company, trucking company, and container depot. And in terms of export procedures at PT. Citra Trans Buana Kargotama Jakarta, the documents that must be fulfilled in the procedure for shipping goods are a packing list, invoice, shipping instruction, bill of loading, certificate of origin, notification of export of goods, and certificate of fumigation.

Flexible yard space allocation plan for new type of automated container terminal equipped with unilateral-cantilever rail-mounted gantry cranes

In this paper, new automated container terminals equipped with Unilateral-cantilever Rail-Mounted Gantry Cranes (URMGC) are considered as the research object. In the scenario, the automated guided vehicles can go deep among the container blocks arranged perpendicularly to the shoreline, which completely changes the yard’s operation mode and affects its operational efficiency. In addition, considering the shortage of storage space in the yard, a flexible space allocation strategy for these yards is studied, and a mixed integer quadratic programming model is established to minimize the horizontal transportation cost of containers. An improved particle swarm optimization algorithm is designed to compensate for the increased complexity of the proposed model. To accelerate the solution speed, the quantity and priority rules are developed to generate reasonable initial solutions, and two velocity updating strategies are adopted to accelerate convergence. Numerical experiments are conducted to validate effectiveness and efficiency of the proposed method, and comparisons with fixed space allocation strategy are presented. The results show that the strategy and solution adopted in this paper can reduce the driving distance of AGVs in such terminal configurations effectively and potentially increase the handling capacity of the yard.

Robust Accurate Lane Detection and Tracking for Automated Rubber-Tired Gantries in a Container Terminal

Lane detection and tracking technique is the autonomous driving basis for Rubber-Tired Gantries (RTGs), vital to the automation and intelligence updating of man-driven container terminals. However, the existing lane detection methods developed for common road scenarios cannot meet the high-precision and robust all-weather requirements of RTG autonomous driving. In this article, we propose an Adaptive Edge-based Lane Detection and Tracking method considering RTG lanes’ characteristics in this paper. First, the candidate edges of lane lines are detected and paired based on the enhanced gradient features. Next, inverse perspective mapping is employed to search the right edges, followed by an adaptive sliding-window method. Ultimately, we develop an adaptive Kalman filter to track lane lines robustly, detecting confidence weighting by relaxing the constraint of lane line width. The proposed method is tested in an actual container yard, the lane centerline’s average position error is 2.051 pixels, and the detection success rate is close to 100%.

Analisis kadar PM10 dan CO serta keluhan pernapasan pada petugas operasional terminal peti kemas PT PELINDO Belawan tahun 2023

Air pollution and respiratory symptoms among operational staff at container terminal of PT. PELINDO Belawan might be caused by emission of PM₁₀ and CO from operational container trucks. This research aims to assess PM₁₀ and CO levels, also to investigate respiratory symptoms among operational staff at container terminal of PT. PELINDO Belawan. This is an observational research with cross-sectional design study. From a population of 699 individuals, 88 samples were obtained using purposive sampling technique. Air quality data was collected through direct measurements at three different locations, while respiratory symptoms data was gathered through staff interviews. PM₁₀ level at the container terminal had exceeded the standard limit, with the highest concentration recorded at the entrance gate, reaching 193 µg/Nm³. Whereas, CO level remained within the acceptable range. Trucks flow observation over a week revealed that the highest flow occurred on Tuesday, with 3,037 trucks, while the lowest flow was on Sunday, with a total of 223 trucks. Among the 88 respondents, 40 individuals (45.5%) experienced respiratory symptoms, with the most common complaint, reported by 25 individuals (65%), being runny or congested nose. Most respiratory symptoms occurred at unpredictable times, as reported by 35 individuals (39.8%). Container terminal of PT. PELINDO Belawan is recommended to enforce mask usage while working and respiratory health check-ups regularly for the operational staff to monitor respiratory health of the operational staff, as well as planting trees to mitigate pollutant levels in the air.

Enhanced Multi-Objective Evolutionary Algorithm for Green Scheduling of Heterogeneous Quay Cranes Considering Cooperative Movement and Safety

Heterogeneous quay cranes (HQCs) are the main energy-consuming equipment of automated container terminals, and they need to move from one bay to another along the rail and maintain a safe distance from one another. Improving the operational efficiency of HQCs and reducing the ineffective walking distance of HQCs are key to reducing the energy consumption of QCs. In this paper, an energy-efficient HQC cooperative scheduling problem is studied, and the HQCs are required to ensure safe and efficient operation. A multi-objective scheduling model is formulated to minimize the maximum completion time of containers, the average completion time of HQCs, and the total energy consumption of HQCs simultaneously. An Enhanced Multi-Objective Evolutionary Algorithm (EMOEA) is designed to solve this problem using a problem-feature-based encoding method to encode and initialize the population, a cooperative strategy to ensure the safe operating distance of HQCs, and a novel multi-objective evaluation mechanism with effective evolutionary operators. The results indicate that the different operational capacities of HQCs had a significant impact on the three studied objectives, especially for some large-scale problems, and that our algorithm outperforms three other well-known multi-objective algorithms in solving the EHQCCSP.

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.

Analysis of Health and Safety (K3), Working Environment and Employee Performance at The Container Depot

This company focuses on operating and managing container depots that provide empty container handling services. The purpose of this study was to identify and analyze the effect of safety and health and work environment on employee performance at this container depot. The method used in this study is a quantitative method, involving 30 respondents using a saturated sampling technique and using a questionnaire measuring instrument (Likert scale) and library research. As well as data analysis using SPSS Version 27 with study methods multiple linear regression analysis, correlation coefficient, coefficient of determination, hypothesis testing using T test and F test. The results of the analysis show that there is a significant positive influence between safety and occupational health and work environment on employee performance with the existence of a multiple linear line equation with a value of Y = 1.860 + 0.367X1 + 0.599X1. The results of hypothesis testing obtained by tcount X1 8.523 and X2 10.160 > ttable 2.048. While the simultaneous test Fcount 57.638> Ftable 3.35. Based on the results of the correlation analysis, there is a positive and strong influence of 81% and 19% is influenced by other factors that are not included in this study.

Discrete-event modelling of container terminal cargo fronts

The basis for designing and upgrading new sea ports and container terminals is regulatory documentation. A part of designing a new sea port is making key technological decisions, including on calculating its cargo throughput capacity. However a method for capacity evaluation of operating ports is not described in the regulatory documents. Operating cargo terminals often undergo significant changes since the moment they were put into operation. Equipment, resources and infrastructure of cargo fronts should not be the only thing taken into consideration when evaluating an existing container terminal capacity. The way in which a terminal interacts with external transport systems (railroad, vessel fleet, etc.) as well as interactions between cargo fronts inside a terminal should also be considered. A discrete- event simulation model for the system consisting of a railroad cargo front, a container yard and a berth cargo front of a container terminal is proposed in the paper. This model allows to evaluate the balance between calls of different modes of transport (vessel calls, cargo train calls), as well as the impact of this balance on the state of container yard and on the terminal cargo throughput capacity in general. Container terminal in terms of proposed model is not merely a set of unrelated objects, but a system. In such system interaction with one of elements has influence on all the others. The model is described as mathematical dependencies between key variables. Cargo train and vessel calls generation is performed via standard spreadsheet methods. To acquire more accurate results, specific sea port statistical data should be used.