Container Terminals Research Articles

Sustainable Synchronization of Truck Arrival and Yard Crane Scheduling in Container Terminals: An Agent-Based Simulation of Centralized and Decentralized Approaches Considering Carbon Emissions

Background: Container terminal congestion is often measured by the average turnaround time for external trucks. Reducing the average turnaround time can be resolved by controlling the yard crane operation and the arrival times of external trucks (truck appointment system). Because the truck appointment system and yard crane scheduling problem are closely interconnected, this research investigates synchronization between the approaches used in truck appointment systems and yard crane scheduling strategies. Rubber-tired gantry (RTG) operators for yard crane scheduling operations strive to reduce RTG movement time as part of the container retrieval service. However, there is a conflict between individual agent goals. While seeking to minimize truck turnaround time, RTGs may travel long distances, ultimately slowing down the RTG service. Methods: We address a method that balances individual agent goals while also considering the collective objective, thereby minimizing turnaround time. An agent-based simulation is proposed to simulate scenarios for yard crane scheduling strategies and truck appointment system approaches, which are centralized and decentralized. This study explores the combined effects of different yard scheduling strategies and truck appointment procedures on performance indicators. Various configurations of the truck appointment system and yard scheduling strategies are modeled to investigate how those factors affect the average turnaround time, yard crane utilization, and CO2 emissions. Results: At all levels of truck arrival rates, the nearest-truck-first-served (NTFS) scenario tends to provide lower external truck turnaround times than the first-come-first-served (FCFS) and nearest-truck longest-waiting-time first-served (NLFS) scenario. Conclusions: The decentralized truck appointment system (DTAS) generally shows slightly higher efficiency in emission reduction compared with centralized truck appointment system (CTAS), especially at moderate to high truck arrival rates. The decentralized approach of the truck appointment system should be accompanied by the yard scheduling strategy to obtain better performance indicators.

Simulation and Optimization of Automated Guided Vehicle Charging Strategy for U-Shaped Automated Container Terminal Based on Improved Proximal Policy Optimization

As the decarbonization strategies of automated container terminals (ACTs) continue to advance, electrically powered Battery-Automated Guided Vehicles (B-AGVs) are being widely adopted in ACTs. The U-shaped ACT, as a novel layout, faces higher AGV energy consumption due to its deep yard characteristics. A key issue is how to adopt charging strategies suited to varying conditions to reduce the operational capacity loss caused by charging. This paper proposes a simulation-based optimization method for AGV charging strategies in U-shaped ACTs based on an improved Proximal Policy Optimization (PPO) algorithm. Firstly, Gated Recurrent Unit (GRU) structures are incorporated into the PPO to capture temporal correlations in state information. To effectively limit policy update magnitudes in the PPO, we improve the clipping function. Secondly, a simulation model is established by mimicking the operational process of the U-shaped ACTs. Lastly, iterative training of the proposed method is conducted based on the simulation model. The experimental results indicate that the proposed method converges faster than standard PPO and Deep Q-network (DQN). When comparing the proposed method-based charging threshold with a fixed charging threshold strategy across six different scenarios with varying charging rates, the proposed charging strategy demonstrates better adaptability to terminal condition variations in two-thirds of the scenarios.

Train assignment and handling capacity arrangement in multi-yard railway container terminals: An enhanced adaptive large neighborhood search heuristic approach

Expanding terminal scale and constructing multiple railway handling yards have become popular strategies for leading railway container terminals globally to cope with the ever-increasing handling volume. Although such an approach greatly enhances the terminal’s productivity, it also intensifies handling operations and introduces additional inter-yard interactions, complicating terminal management. To address these challenges, this paper investigates an integrated optimization approach for multi-yard railway container terminals, which feature both rail-road and rail-rail container transshipment operations. The train assignment plan for each yard and the handling capacity arrangement for each train are jointly optimized while considering inter-yard container transits, workload allocation for yards, and safety requirements in train shunting. This problem is formulated as a nonlinear programming model, with the objective to minimize operational delay and service time for each incoming train, and to minimize workload differences and container transit volume among yards. To efficiently solve this problem, this research develops an enhanced adaptive large neighborhood search (EALNS) heuristic, which includes several customized operators and feasibility repair methods, and is further enhanced with a local search method and backtracking mechanism compared to the standard ALNS framework. Computational experiments with different data scales and problem settings demonstrate the superiority of the EALNS in terms of solution quality and stability compared with three other solution methods. Additionally, practical insights for terminal operations are drawn through detailed analysis of different infrastructure configurations, transshipment train characteristics, and unit cost settings.

Collaborative Optimization of Vessel Stowage Planning and Yard Pickup in Automated Container Terminals

The aim of this research is to minimize the number of container-rehandling operations in both the yard and on the ship in order to solve the problem of coordinated optimization of ship loading and yard container retrieval and enhance the loading efficiency of automated container terminals,. An optimization model that integrates the optimized decision-making of both the container retrieval order from the yard and the ship’s space allocation is developed, and an improved cuckoo algorithm is employed to solve the optimization problem. This paper examines the influence of container retrieval order from the yard on rehandling within the yard, as well as the effect of the ship’s space allocation on subsequent rehandling operations at the unloading port. Experimental results demonstrate that the solution derived from the comprehensive optimization model based on the improved cuckoo algorithm considerably reduces the overall number of overturned containers. This confirms that the proposed optimization model effectively enhances loading efficiency and reduces container rehandling both in the yard and on the ship. The analysis of experimental results indicates that the model and algorithm proposed in this paper have certain applicability.

A three-stage heuristic for optimizing container relocations in maritime container terminals

The Container Relocation Problem (CRP) is one of the most important optimization problems in maritime container terminals. The objective is to minimize the number of relocation operations for retrieving containers in a sequence. If the container to be retrieved next is not at the top of a stack, unproductive relocations have to be carried out. Due to the large number of containers handled by busy terminals, a slight reduction in relocation rates can result in significant savings in operating costs. Most of the existing heuristics make relocation decisions for the blocking containers one by one, based on simple indicators. In this article, we propose a Three-Stage Heuristic (3SH) that extends the decision horizon to multiple containers to achieve a higher-quality solution. Computational experiments are conducted on 3 sets of benchmark instances, and the results show that the proposed heuristic outperforms the state-of-the-art heuristics documented in the research literature.

Exploring service quality of inland container depot-empirical evidence from the Red River Delta, Vietnam

Inland Container Depots (ICDs) are inland multi-modal terminals where goods in intermodal loading units can be transferred directly to seaports. The contribution of ICDs to regions’ economic and social growth is undeniable. To achieve the sustainable development of ICDs, evaluating and improving their service quality is critical. This study aims to investigate the factors contributing to the service quality of ICD in a developing country. The data utilized covers some ICDs in the Red River Delta, Vietnam. Regarding analytic methods, descriptive statistics first were run to show the level of aspects of service quality of ICDs. Subsequently, attitudinal statements were analyzed using exploratory factor analysis before linear regression was applied to recognize the factors influencing the service quality of ICDs. Generally, the service quality of ICDs was evaluated at an acceptable level but far from the high one. The results suggested that the four influential service quality factors included location and accessibility, facilities, process and management, and labor. Based on the findings of contributing factors, managerial implications were proposed.

Integrated Scheduling of Handling Equipment in Automated Container Terminal Considering Quay Crane Faults

Quay cranes (QCs) play a vital role in automated container terminals (ACTs), and once a QC malfunctions, it will seriously affect the operation efficiency of ships being loaded and unloaded by the QC. In this study, we investigate an integrated scheduling problem of quay cranes (QCs), yard cranes (YCs), and automated guided vehicles (AGVs) under QC faults, which is aimed at minimizing the loading and unloading time by determining the range of adjacent operational QCs of the faulty QCs and reallocating unfinished container handling tasks of QCs. A mixed integer programming model is formulated to dispatch QCs, YCs, and AGVs in ACTs. To solve the model, an adaptive two-stage NSGA-II algorithm is proposed. Numerical experiments show that the proposed algorithm can significantly reduce the impact of faulty QCs on productivity while maintaining its synchronous loading and unloading efficiency. The sensitivity analysis of ship scale, location, and number of faulty QCs indicates that the number of faulty QCs has a greater influence on the loading and unloading efficiency than their locations, and the impact of faulty QCs on the efficiency of small-scale ships is greater than that of large-scale ships.

Investigation of some issues of automation of elements of terminal complexes for transshipment of large-capacity containers

The topic of the work is the study of the reasons for increasing the efficiency of the use of marine container transportation in the entire supply chain. It is noted that the increase in their efficiency is explained by the possibility of transporting various types of cargo, the speed of handling vehicles, as well as the compactness of storage and safety of cargo. The problem of increasing ship capacity on the terms of shipping companies, which currently exists and is being solved by container terminal operators, has been formulated, which allows minimizing the time of ships parking in the port for processing, which in turn can be achieved by increasing the capacity of ships. Attention is drawn to the fact that reducing costs by increasing the efficiency of lifting and transport equipment stimulates investments in automation systems for almost all terminal operations, and in particular in lifting and transport equipment systems. It is emphasized that the automation process of container terminals differs depending on the task at hand (a new project is being considered or work is being carried out to automate an existing terminal). The implementation of automation at existing terminals is a more difficult task due to the problems of compatibility with the types of activities performed and resistance to ongoing changes, which primarily involve systematic and repetitive technological processes that can be programmed. Attention is drawn to the fact that container terminals use the latest operating systems to control and optimize the movement of containers inside the warehouse area (in particular, they are used at terminals where gantry cranes on a pneumatic (RTG) and on a rail (RMG) are used), and it is also emphasized that when working with RTG technology gantry cranes on a pneumatic vehicle are equipped with sensors connected to satellite positioning systems, which are located on the terminal area and on wheeled carts and are brought to the place of cargo operation by signals from the control room, at the same time, the dock operator controls only when lowering or lifting the container. Such information systems are also used on terminals operating using RMG technology. It is noted that automation of berthing container cranes is currently under development, since the complexity of its implementation lies in the fact that during pitching the vessel has a roll and a deflector, therefore, when moving it, it is difficult to determine the exact location of the container and the alignment of the spreader horizon with the container horizon, as a result, the guidance process? It requires additional time, which leads to a decrease in work productivity.

Assessment of the Position of North Adriatic Terminals in Container Market Based on Different Indices

Background: This paper addresses the common question of how service providers compare to their competitors and what their competitive advantages are. It focuses on the North Adriatic ports of Trieste, Koper, Rijeka, Venice, and Ravenna, all members of the North Adriatic Ports Association, analyzing their position, size, competitiveness, and role in the container market. Methods: The research employs three distinct methods: market structure analysis using several concentration indices, the R method for ranking terminals, and aggregation of these indices to create a combined index for port performance. Results: Based on the rankings, indicators, the BCG matrix, and future development plans for each terminal, the ports are ranked as follows: Koper, Rijeka, Trieste, Venice, and Ravenna. Koper emerges as the leader, positioned in the high market share and strong growth category. This advantageous position allows Koper to efficiently attract traffic without requiring substantial investments. Conclusions: The contribution of the work is that the specific measure indices were applied, which were not used in the analysis of the North Adriatic container terminals until now. The research provides both a broad and detailed understanding of the position, role, and condition of each terminal. This insight enables stakeholders to take timely, strategic actions aimed at boosting productivity and traffic, ultimately improving their competitive standing.

Prediction of delivery truck arrivals at container terminals: an ensemble deep learning model

Prediction of delivery truck arrivals at container terminals: an ensemble deep learning model

Simulation-based evaluation of road transportation logistics in a dry port with topographic challenges

The extension of existing container terminals or the creation of new ones introduces new logistical challenges, including topographic issues and increased distances between the quays and storage yards located several kilometers away from the quay (dry port). These challenges are complex to evaluate analytically and directly impact the acceleration, deceleration, and average speed of a truck which in turn affect the productivity and synchronization of the overall terminal logistics. This paper proposes a transportation simulation model that incorporates detailed descriptions of the topographical and geometrical restrictions. Our simulation model evaluates various scenarios for container transportation logistics, including varying road design terminals and truck fleet size to enhance productivity. A case study from a potential container terminal on Canada’s St. Lawrence River is used to demonstrate the simulation model. Several scenarios with different designs are tested and the simulation provides numerical results for supporting decision makers.

Security Risk Assessment in Container Terminals: Empirical Evidence from Greece

Security Risk Assessment in Container Terminals: Empirical Evidence from Greece

The Influence of Intelligent Guided Vehicle Configuration on Equipment Scheduling in the Railway Yards of Automated Container Terminals

The Influence of Intelligent Guided Vehicle Configuration on Equipment Scheduling in the Railway Yards of Automated Container Terminals

Evaluating the Impact of Private Sector Participation on Operational Efficiency in Container Terminals: A Case Study of Colombo Port

Sri Lanka, strategically located in South Asia, has the potential to become a significant hub for international maritime trade. However, the current port infrastructure, particularly in Colombo, faces capacity constraints that limit its ability to accommodate larger vessels and manage increasing container traffic. This study evaluates the impact of private sector participation on the operational efficiency of Colombo’s container terminals - Jaya Container Terminal (JCT), South Asia Gateway Terminal (SAGT), and Colombo International Container Terminal (CICT). Using Key Performance Indicators (KPIs) and Data Envelopment Analysis (DEA), the study found that private sector involvement significantly enhances terminal efficiency. SAGT, a privately operated terminal, exhibited the highest overall efficiency, while CICT demonstrated the highest productivity. JCT, though publicly operated, showed commendable performance but lagged behind the private terminals. The findings emphasize the value of public-private partnerships (PPPs) in optimizing port operations, offering critical insights for policymakers and stakeholders aiming to strengthen Sri Lanka’s maritime economy.

Optimization berth allocation in container terminals: A Pyomo and Google Colab approach

Efficient berth allocation profoundly influences container terminal operations, affecting vessel waiting and turnaround times, and overall performance. This study presents a mixed-integer linear programming (MILP) model addressing the Berth Allocation Problem (BAP) in a Malaysian container port. By incorporating the Pyomo optimization library and CBC (Coin-or Branch and Cut) solver in Google Colab, optimal berth allocations are determined, minimizing vessel turnaround times. Visualized in a Space-Time diagram, the results highlight efficient allocation strategies. Despite limitations, the study optimally resolved three instances, achieving a remarkable 38.54% reduction in overall vessel turnaround time compared to FCFS (First-Come-First-Serve) allocation. By prioritizing port turnaround time, the optimization substantially reduced berthing and departure delays, aligning with UNCTAD's call for enhanced port efficiency and accelerated decarbonization efforts.

A dynamic yard space reservation algorithm based on reward-penalty mechanism

Increasing throughput at container terminals leads to higher yard occupancy rates, reduced yard service capacity, and inefficient use of space. These issues result in longer waiting times for trucks, underutilized yard slots, and longer distances between berth positions and the yard, particularly under high occupancy conditions. Traditional methods for allocating yard space fail to adequately consider dynamic container arrival patterns, conflict between container operations, and efficient use of yard resources. This paper introduces an innovative approach to improve yard efficiency by dividing yard container retrieval into time intervals and dynamically reserving yard slots within each interval. This method aims to minimize operational conflicts, reduce distances between blocks and berths, and avoid excessive reservations. We propose a dynamic reservation algorithm based on a reward-penalty mechanism to handle the problem's complexity and real-time demands. Furthermore, a time-series reward-penalty mechanism, which considers past reservation feedback and future reservation potential, ensures the concentration and continuity of container groups in the yard. Our evaluation metrics and multiple experimental scenarios demonstrate that this method significantly enhances yard efficiency and overall port productivity compared to static and other dynamic algorithms.

Advances in terminal management: simulation of vehicle traffic in container terminals

AbstractControlling and managing traffic flows on internal roads in container terminals are crucial in achieving expected productivity levels and reducing negative externalities caused by congestion inside and outside the terminal areas. This paper proposes a simulation approach which terminal operators can use as a decision-support tool to assess the effects of their management strategies and improve terminal performance, resilience, and sustainability. A microscopic traffic simulation approach models key operations of a typical container terminal affecting road traffic flows. In particular, to estimate quantitative indicators, an import truck process is reproduced, considering the overlapping of the external truck and internal trailer flows. To measure environmental impacts, the model is extended with an instantaneous emissions model linked directly to the step-by-step traffic data. The proposed method is tested on a sector of the PSA Genova Pra’, the main Italian container gateway terminal. Performance indicators related to the terminal’s efficiency and sustainability are estimated, to compare alternative scenarios considering possible operational configurations and disturbance events, such as the closure of a part of the yard. By focusing on the interactions between vehicle flows and terminal equipment operations, this approach offers a new perspective on terminal operations, oriented both towards container terminal operators and stakeholders, such as road hauliers.

Research on Energy Saving Effect of Parallel and Perpendicular Yard Layouts under Different Proportions of Transshipment at the Automated Container Terminal

The proportions of container transshipment is the key factor in determining the proportion of automated guided vehicle (AGV) and external container truck operations. In terms of parallel and perpendicular layouts of automated container terminals (ACTs), varying proportions of container transshipment result in different proportions of AGVs and external container truck operations, subsequently leading to distinct impacts on energy consumption (EC) for each ACT layout. This paper deemed EC as the primary evaluation criterion, established an EC model encompassing yard cranes (YCs) and container trucks, and investigated the EC of parallel and perpendicular layouts at different proportions of container transshipment. The results indicate that when the proportions of container transshipment were less than 17%, the parallel layout had lower EC; when it was between 17% and 21%, there was not much difference between the two layouts; when it was greater than 21%, the perpendicular layout had lower EC. This conclusion was based on an ideal environment established in this paper. When making decisions, decision makers should use this model as a starting point and adapt it flexibly to the actual situation of the port, in order to arrive at a reasonable and feasible plan.

Research Progress and Hot Frontier Analysis of Container Terminal Transportation Operations

Using CiteSpace software and bibliometric method, 652 articles related to container terminal transportation operations in WOS core collection database were visualized and analyzed. Based on the network knowledge graph of document distribution of time and space, core author, research institution and key words, this paper analyzes the overall distribution, research hotspot, evolution context and frontier trend of container terminal transport operations research, in order to enrich the perspective of container terminal transport operations review study, and provide reference for promoting the construction of container terminals in our country.

Evaluating Vietnam's container terminal efficiency considering carbon neutrality

This paper aims to assess container terminal (CT) efficiency with the effect of carbon neutrality. Among mechanisms to achieve carbon neutrality in CTs' operations, emission taxes are deemed the most preferred tool to internalize the external costs associated with greenhouse gas emissions by placing a financial burden on polluters. This paper first uses cluster analysis to determine the homogeneous decision-making units (DMUs), i.e., container terminals. A novel approach is proposed to determine the level of emission taxes that DMUs should be levied based on how much CO2 they discharge. Since emission taxes are an undesirable output from the operations of CT operators (CTOs), the Slacks-based Measure Data Envelopment Analysis (SBM-DEA) model is thus employed to incorporate the emission taxes into the research model and to determine the optimal emission taxes for CTOs. Finally, the CTOs in Vietnam (hereafter the VN-CTOs case) are empirically surveyed to verify the proposed model. The proposed research framework can contribute a methodological reference toward the relevant literature in achieving carbon neutrality. Further, the empirical results can provide practical information for the Vietnamese CTOs to improve their CT efficiency.