Terminal Operations Research Articles

A multi-agent reinforcement learning approach for ART adaptive control in automated container terminals

Intelligent transportation equipment represented by Artificial Intelligence Robot of Transportation (ART) has been gradually applied to automated container terminals (ACT). ARTs have higher intelligence and distributed autonomous decision-making capability compared to AGVs. The production and operation of ACT require strict loading plans based on container types and destination ports, which puts strict requirements on the ART loading task sequence. ART travel time from the yard to the quay is highly uncertain due to special scenarios such as traffic flow convergence and turning in narrow areas, which will lead to long waits for ART due to out-of-sequence arrivals at the quay. Therefore, it is necessary to regulate the speed of ART to adjust the timing of ART arriving at the quay. However, existing scheduling systems tend to ignore the impact of ART speed and loading sequence constraints on terminal operations. To optimize the multi-ART control problem of ACT, the waiting time of ART at the quay is taken as the optimization goal, and the speed regulation of ART during each task is defined as a Markov decision process. Then, by incorporating reinforcement learning and a multi-agent approach, an adaptive decision-making method is developed to generate the optimal speed regulation strategy. This method interacts with the multi-agent simulation environment to obtain real-time status information and learns strategies online to improve the intelligence of individual agents and the collaborative capabilities of the agent group. Finally, a multi-agent simulation model embedded with a reinforcement learning agent is established on AnyLogic software. Simulation results show that this method can effectively reduce the waiting time of ART, improve the coherence and efficiency of loading operations, and exhibit good performance in online scenarios that consider emergency tasks. The results indicate that the speed of ART in ACTs with parallel layout of the yard can impact the operational efficiency of the system. Furthermore, by appropriately defining the reward function and training method, collaborative behaviour among equipment can be enhanced, ultimately optimizing the overall performance of the system.

Intermodal Transportation Challenges in Eastern Europe: Case Study of Romania

Abstract The purpose of this paper is to analyze data from the Romanian intermodal transportation sector and provide an overview of its main terminals (sea, river, road and rail) and the operational challenges faced by its most important logistics service providers. Intermodal transportation (by rail) is encouraged at EU level as a sustainable alternative to current predominant truck haulage. Most research articles outline issues with connectivity, terminal handling infrastructure and cost efficiency as factors hindering large scale adoption. Other authors tend to emphasize the more reliable delivery schedules, reduced road congestion and emissions as drivers of cost competitiveness on medium term. Relevant cargo volume traffic (tons, TEU and ITU) is analyzed at Romania’s main intermodal hubs in the last 10 years (2014-2023) using quantitative and qualitative data to provide a comprehensive overview of its overall competitiveness in this sector. Most Eastern European countries are faced with the same challenge in terms of intermodal transportation: the shortcomings of their supporting network due to insufficient public investment, highlighted by the results from Romania (case study method). Main results show Constanta Port had record cargo traffic in 2023, but its throughput is hindered by constant congestion issues, similar to the highly competitive road sector where intense truck traffic creates bottlenecks on the major roads leading to Western Europe. Cargo is also shipped via the Danube and freight trains, but to a limited extent due to low average speeds and inconsistent reliability along most sectors. The paper highlights the importance of a country’s strategic hubs and their connectivity (sea and/or river ports, main railway lines and road sectors) as a source of future growth and development perspectives, for terminal operators as well as neighboring regions (EU and EEA) through increased business activity.

Insights into How to Enhance Container Terminal Operations with Digital Twins

The years 2021 and 2022 showed that maritime logistics are prone to interruptions. Ports especially turned out to be bottlenecks with long queues of waiting vessels. This leads to the question of whether this can be (at least partly) mitigated by means of better and more flexible terminal operations. Digital Twins have been in use in production and logistics to increase flexibility in operations and to support operational decision-making based on real-time information. However, the true potential of Digital Twins to enhance terminal operations still needs to be further investigated. A Delphi study is conducted to explore the operational pain points, the best practices to counter them, and how these best practices can be supported by Digital Twins. A questionnaire with 16 propositions is developed, and a panel of 17 experts is asked for their degrees of confirmation for each. The results indicate that today’s terminal operations are far from ideal, and leave space for optimisation. The experts see great potential in analysing the past working shift data to identify the reasons for poor terminal performance. Moreover, they agree on the proposed best practices and support the use of emulation for detailed ad hoc simulation studies to improve operational decision-making.

Flowfield Analysis of Vortex Interactions During Large Sharp-Edged Gusts

Uncrewed air vehicles in urban environments will have flights during terminal operations that are dominated by strong transient aerodynamics. These vehicles are not only lighter and smaller than traditional rotorcraft and helicopters, but in many instances they may be hybrid configurations with lifting surfaces similar to those of fixed-wing aircraft. These differences require further understanding of the physics of these transient aerodynamics, specifically large-amplitude transverse gusts and the resulting vehicle response, where classic indicial theory is no longer valid. This is crucial to the safety and certification of these air vehicles near buildings and populations. Prior efforts identified that gust responses depart from traditional linear theory when the leading-edge vortex (LEV) forms as a distinct feature and departs from the lifting surface, resulting in flow nonlinearities. This paper expands our understanding of the interactional physics of these nonlinear transverse gusts with flow separation. LEV and trailing-edge vortex (TEV) behavior are correlated, and these vortex interactions are studied to understand the impact on flow separation and subsequent aerodynamic behavior. Larger gust ratios are observed to increase the LEV normal translation, while flow separation is driven by the location and magnitude of the TEV.

A Novel Auction-Based Truck Appointment System for Marine Terminals

Background: Increased maritime trade has led to a surge in drayage operations, causing congestion and environmental issues in port areas. Truck Appointment Systems (TASs) are commonly used to manage truck arrival rates, yet transparency and equity in slot allocation remain problematic, fostering distrust between Licensed Motor Carriers (LMCs) and Marine Terminal Operators (MTOs). Methods: This study proposes a polycentric approach to improve truck scheduling and ensure that those impacted by decisions are involved in the decision-making process. A single-round auction mechanism focused on optimizing the truck hauling process through a pricing policy that promotes sincere bidding is introduced. The proposed approach employs an optimization strategy to achieve equitable coordination in truck synchronization through means of adaptable capacity management. Results: Numerical experiments assessing scenarios of noncollaborative behavior against partial collaboration between MTOs and LMCs demonstrate the effectiveness of the proposed approach in enhancing user satisfaction and terminal conditions for a case study focused on a medium-sized terminal. Collaboration between trucking companies is shown to increase utility per monetary unit spent on slot acquisition. Conclusions: The polycentric strategy offers a solution to TAS limitations by ensuring stakeholder participation with respect to flexibility and transparency by ensuring that those impacted by decisions are involved in the decision-making process.

Assessing the Digital Transformation in the Maritime Transport Sector: A Case Study of Croatia

In this research, the authors investigated the factors of digital transformation in the maritime transport sector, which were applied to the case study of Croatia. Since there is a pronounced lack of research dealing with the digital transformation factors in the maritime transport sector both globally and in Croatia, as a first step the authors identified the aforementioned factors using the literature review method and interviews. Moreover, the survey was carried out among a representative group of stakeholders involved in the maritime transport sector in Croatia, including administrative entities such as port authorities, ministries, and harbormaster’s offices, as well as commercial participants such as freight forwarders, agents, and terminal operators. The goal was to obtain the state of the art of digital transformation in the maritime transport sector. A total of 94 organizations provided valid responses. Finally, the authors proposed measures to improve the digital transformation in the maritime transport sector in Croatia. The results highlighted the importance of various digital transformation factors, such as information security, investment in emerging technologies, leadership motivation, and expertise. The case study presented serves as a valuable reference for comparable countries that recognize their resource constraints but aspire to enhance their efficiency and competitiveness.

Multiagent Q-Learning Approach for the Recharging Scheduling of Electric Automated Guided Vehicles in Container Terminals

In recent years, advancements in battery technology have led to increased adoption of electric automated guided vehicles in container terminals. Given how critical these vehicles are to terminal operations, this trend requires efficient recharging scheduling for automated guided vehicles, and the main challenges arise from limited charging station capacity and tight vehicle schedules. Motivated by the dynamic nature of the problem, the recharging scheduling problem for an entire vehicle fleet given capacitated stations is formulated as a Markov decision process model. Then, it is solved using a multiagent Q-learning (MAQL) approach to produce a recharging schedule that minimizes the delay of jobs. Numerical experiments show that under a stochastic environment in terms of vehicle travel time, MAQL enables the exploration of better scheduling by coordinating across the entire vehicle fleet and charging facilities and outperforms various benchmark approaches, with an additional improvement of 18.8% on average over the best rule-based heuristic and 5.4% over the predetermined approach. Funding: This work was supported by the National Natural Science Foundation of China [Grant 72101203], the Shaanxi Provincial Key R&D Program, China [Grant 2022KW-02], and the Singapore Maritime Institute [Grant SMI-2017-SP-002]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0113 .

The influence of management functions on the productivity of yard cargo handling equipment in container terminals

PurposeThis empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.Design/methodology/approachBy closely examining crucial management aspects such as planning, organizing, leading, and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).FindingsThe findings of this study demonstrate that planning (PL), organizing (OR), and controlling (CT) significantly contribute to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.Originality/valueTheoretically, this study contributes by providing clarity to the definition, purpose, and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.

The impact of container call size - evidence from simulation modelling

We present an analysis of the impact of large container ship call sizes on the operational efficiency of container terminals as well as on hinterland modes of transport. We use standard container terminal simulation software, that can represent a realistic terminal operation. We include dynamic crane productivity, arrival time uncertainty, and deepsea vessel prioritisation in our model.Our experiments investigate the impact of introducing larger call sizes of container ships, increasing the uncertainty in arrival times of deepsea ships, and the impact of the phenomenon of split calls that are employed by the largest container ships in certain regions in the world. We differentiate between the impact on terminal operations, land-based hinterland traffic, and hinterland traffic over water, through barges and feeder vessels.Our results show that introducing large ships with large container call sizes comes with benefits and drawbacks. Benefits can be found in planning advantages for both the deepsea ships and barges and feeders handled in the terminal. Drawbacks occur as a result of operational peaks in subsystems such as the quay cranes, the stack and the land side gates. Higher uncertainty deteriorates the performance of the terminal, but the impact on the hinterland modes of transport is greater than on the large deepsea vessels. The impact of the split call is that it brings all the disadvantages of large vessels, but none of the benefits.Our analysis shows the operational impact of large call sizes on terminal operations and hinterland transport operations, based on container terminal simulations with a higher degree of realism than previous work. In addition, we offer, for the first time, insights in the impact of split calls of container ships at container terminals.

Integrated rescheduling optimization of berth allocation and quay crane allocation with shifting strategies

Container terminal operations are a core aspect of vessel operations in ports and necessitate an intelligent rescheduling approach to manage complex uncertainty scenarios. This paper investigates the problem of berth allocation and quay crane (QC) assignment with shifting strategies. A variable-length rolling mechanism (VLRM) is designed to identify uncertainty scenarios and determine the optimal rescheduling time point. Notably, we introduce a novel cross-wharf shifting movements strategy (CWSM) and develop a rescheduling model that accounts for constraints related to tidal time windows. The proposed Adaptive Large Neighborhood Search algorithm (ALNS) is tailored to solve this problem effectively. Computational results from various instance sizes validate the efficacy of both the model and the ALNS algorithm. These results demonstrate that the ALNS algorithm exhibits distinct advantages in solution quality and computational time for large-scale instances. Furthermore, the inclusion of tidal time window constraints significantly amplifies the complexity of uncertainty scenarios, emphasizing their importance and the impossibility of neglecting them. The cross-wharf shifting movements strategy, presented herein, effectively mitigates the impact of uncertainty scenarios within a defined scope while enhancing adjustment flexibility.

Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: a DEA approach

Container ports play a pivotal role in international trade, facilitating the movement of goods and fostering economic development. While much attention has been given to the efficiency of ports in high-income countries, container ports in lower-middle-income (LMI) countries have received less attention. This paper addresses this research gap by assessing container ports' operational efficiency across diverse LMI countries and determining ways for their efficiency enhancement and management optimization. The cross-sectional data for the year 2012 was collected for 53 container ports in LMI countries. This research utilizes data envelopment analysis, which offers the advantage of considering multiple inputs and outputs. The results show that the overall technical inefficiencies of LMI countries' container ports are mainly due to pure technical inefficiency rather than scale inefficiencies, and the most efficient ports have a combination of large and hub ports. They also reveal that larger ports (as measured by throughput) are not necessarily more efficient than ports with a small production scale. The results of this research can provide government authorities, port authorities, terminal operators, and investors with valuable insights into resource allocation, competitive advantage, and optimization of operating performance.

Расчет эксплуатационных расходов с учетом транспортно-технологической схемы и параметров оборудования контейнерного терминала

A method for evaluating the performance distribution of transshipment equipment performing operations in a container terminal stack is considered. It is proved that the productivity of operations is the most significant indicator for assessing the economic efficiency of a marine or dry container terminal. Performance evaluation is carried out on the assumption that the technological task for reloading equipment is a sequence of containers with random coordinates in a stack. To complete this technological task, the reloading equipment must move from the position of the last task to the position of the new one. For each movement in operation, the speed is calculated taking into account the acceleration and braking of the mechanisms. As an example of performance evaluation, a warehouse container crane with pneumatic wheels, related to overhead handling equipment, is considered. This type of equipment is the most common in modern container terminals. A description of the simulation model that is used to perform the assessment is provided. The initial data of the model on the execution time of individual movements, as well as on the parameters of the stack, were collected at Russian container terminals. A description of the simulation model that is used to perform the assessment is provided. The initial data of the model on the execution time of individual movements, as well as on the parameters of the stack, were collected at Russian container terminals. The results of the simulation model are the probability distribution of the performance of transshipment equipment during the selection and stacking of containers in the stack of the container site. It is established that the results obtained agree with the actual data on the operation of Russian container terminals. The proposed method makes it possible to more accurately assess the performance of reloading equipment. It is noted that the developed approach should be supplemented taking into account container warehousing strategies, as well as methods of algebraic estimation of the complexity of container sampling.

Experience analysis of automation and robotization of the container terminal operation

The paper reviews the existing approaches to automation of both transshipment equipment and technological operations performed at container terminals. It is pointed out that automation and robotization of warehousing and port operational processes is one of the current global trends in the development of cargo transshipment and temporary storage technologies at seaport berths. Therefore, the search, accumulation and systematization of a lot of information about practical developments in this area of transport industry is one of the scientific tasks in choosing the direction of the dissertation research "Technology, arrangement and management of transshipment processes in ports". On the basis of the studied domestic and foreign experience in the field of arrangement of the management system of the sea container terminal the operational processes in which the object of automation was transshipment technology were classified. The unification of individual methods of automation of operational processes into groups (levels of automation) was made on the basis of the classification criteria "the number of automated equipment units ". Unstructured data presented as primary source information on the websites of manufacturers of transshipment equipment, as well as secondary open scientific data were the sources of information for the scientific research.

Gate appointment design in a container terminal: A robust optimization approach

Gate congestion is a main challenge faced by container terminals worldwide. In the scenario of gate congestion, the long waiting line of container trucks can block the traffic into the terminal, leading to disrupted terminal operations and unsatisfactory operating efficiency. In this paper, we study a gate appointment design problem that aims to manage the number of trucks allowed to a container terminal over time, so as to minimize the length of the truck waiting line and alleviate gate congestion. To optimize the gate appointment strategy, the truck service plans need also be devised, which involve the decisions for assigning trucks to yard blocks for container transhipment. We develop a two-stage robust optimization model for the problem by taking into account the uncertain service capacities of the yard blocks. Our model considers two decision stages, where the first-stage decision allocates slot capacities for the appointment slots, whereas the second-stage decision designs truck service plans with observed yard service capacity. We solve the two-stage robust model using an adapted column-and-row generation algorithm. In each iteration of the adapted column-and-row generation algorithm, the second-stage decision is generated by means of a pseudo-polynomial-time dynamic programming algorithm, while the first-stage decision is generated by a tailored scenario decomposition method. We test the computational performance of the proposed solution method on instances generated from real terminal operation data, and reveal managerial insights that would inspire terminal operators in the management of truck appointment for gate congestion mitigation.

Analysis of Safety Hazards and Implications for Container Port Terminal Operations in Nigeria

Port operations in Nigeria have come a long way in terms of growth, with significant shipment turnovers occurring annually. However occupational hazards including falls from heights, lifting mishaps, mooring mishaps, slips and trips as well as human fatigue occurring during field operations which pose significant risks affecting the safety and performance of operations. This study aggregates data from port workers in six (6) container terminals within Nigeria in order to determine the magnitude of these occupational hazards being faced and juxtapose the role of the terminal operators in balancing service efficiency with safety. Convenience sampling technique was deployed for this survey while primary data was collected through the use of closed-ended questionnaires. A total of 340 questionnaire responses from APM Terminal Ltd, Josepdam Port Services Ltd, Five-Star Logistics, WACT, Ecomarine Nigeria Ltd, and Green Leigh Nigeria Ltd., were analyzed for operational risk factors using percentages. Chi-square analysis was used to test the postulated hypothesis which sought a relationship between frequency of occupational hazard and years of field experience. The null hypothesis was accepted (P > 0.05) and hence inferred that hazard occurrence over the years was independent of field experience. The result suggests a holistic implementation of safety regulations including the use of technology as a measure to curb operational hazards.

Analysis of Constraints against Efficiency of Seaport-hinterland Logistics in Nigeria

Having realized that most Nigerian seaports are congested and the problem of moving goods have been difficult, the Federal Government through Bureau of Public Enterprises and Nigerian Shippers’ Council were mandated to identify Inland Container Depots (ICDs) and Container Freight Stations (CFSs) across the country with connectivity to rail transport. Since 2004 to date, these have mostly not been functioning. This paper therefore examined the constraints and possible factors responsible. The Nigerian Ports Authority, Road Haulage Association, Terminal Operators, selected Shipping companies were used as respondents. 34.1% (253) from the population of 743 respondents were sampled with the use of Cochran formula and stratified random sampling technique. Shaphiro Test and multiple regression were used to analyze the constraints against the use of ICDs and CFSs. Principal Component Analysis was used to extract the major factors hindering port-hinterland logistics in Nigeria. It was observed that 50% of general logistics constraints emanated from lack of efficient rail system, enforcement and finance combined. Extracted causative factors against port-hinterland movements of goods are: inadequate terminal capacity, parking and inadequacy of cargo handling facilities. The research concluded that both general constraints and causative factors are to be looked into with stringent policy enforcement.

A survey on computational intelligence approaches for intelligent marine terminal operations

AbstractMarine container terminals (MCTs) play a crucial role in intelligent maritime transportation (IMT) systems. Since the number of containers handled by MCTs has been increasing over the years, there is a need for developing effective and efficient approaches to enhance the productivity of IMT systems. The berth allocation problem (BAP) and the quay crane allocation problem (QCAP) are two well‐known optimization problems in seaside operations of MCTs. The primary aim is to minimize the vessel service cost and maximize the performance of MCTs by optimally allocating berths and quay cranes to arriving vessels subject to practical constraints. This study presents an in‐depth review of computational intelligence (CI) approaches developed to enhance the performance of MCTs. First, an introduction to MCTs and their key operations is presented, primarily focusing on seaside operations. A detailed overview of recent CI methods and solutions developed for the BAP is presented, considering various berthing layouts. Subsequently, a review of solutions related to the QCAP is presented. The datasets used in the current literature are also discussed, enabling future researchers to identify appropriate datasets to use in their work. Eventually, a detailed discussion is presented to highlight key opportunities along with foreseeable future challenges in the area.

Method of Reducing Energy Consumption during Forklift Operator Training in Cargo Terminals Utilizing Virtual Reality

In the era of shrinking resources of traditional fossil fuels and the increasingly dominant sustainable development policy, actions are taken to reduce energy consumption as much as possible, assuming that we achieve identical operational goals. These activities are apparent in the industries with the most significant energy demand, i.e., the aviation industry. To achieve this, these industries implement modern technologies in all possible areas of operation. One of these areas is the area of operator training, especially the most energy-consuming devices and types of equipment. This article investigated the potential of virtual reality (VR) technology for energy optimization of forklift operating training in airport cargo terminals. The authors propose a method whose practical implementation in one of the cargo terminals reduced energy consumption by several times while training forklift operators. The added value is that the method is universal and, after appropriate modification, can be used to train operators of other devices. The study compared traditional training methods with a VR-based training approach, assessing their impact on energy consumption and overall efficiency of forklift operations in airport cargo terminals. The results prove that VR technology training can significantly reduce energy consumption while improving operational efficiency and can offer a sustainable and effective training solution for the entire logistics sector.

Analysis of the Overhead Crane Energy Consumption Using Different Container Loading Strategies in Urban Logistics Hubs

This study addresses the critical gap in the literature regarding the energy efficiency of intermodal terminals in smart cities, mainly focusing on crane operations during train loading processes. Novelty’s contribution lies in developing a comprehensive simulation model in FlexSim, where quantitative analysis of crane energy consumption, factoring in container location in the storage yard, rehandling operations, and crane movement strategies were performed. Moreover, the analysis of hoist, trolley, and gantry movements was performed to evaluate their impact on overall container loading process energy efficiency. The findings reveal that the choice of train loading method significantly influences crane energy consumption, thereby affecting the operational costs, environmental footprint, and energy efficiency of the logistics hub in the form of an intermodal terminal. This research provides a methodology for assessing and enhancing the energy efficiency of intermodal terminals and highlights the broader implications for smart city sustainability goals, including reduced greenhouse gas emissions, lower operating costs, and improved transportation infrastructure. The outcomes of this research can possibly support smart city planners and logistics managers in making informed decisions to optimise intermodal terminal operations, contributing to urban areas’ sustainable development and economic resilience.

A timely efficient and emissions-aware multiobjective truck-sharing integrated scheduling model in container terminals

In line with the development of green port terminals and the necessity of environmentally friendly efficient use of handling and transportation equipment, criteria such as emission reduction, energy minimization, and efficiency in a container terminal are prominent issues, which in recent years, have been the main concern of container terminal managers in developing terminal operating systems. Therefore, in this study, a bi-objective mixed integer mathematical programing model of integrated scheduling for ships’ loading and unloading operation sequencing in container terminals is proposed, which considers the minimization of containers’ flow time, trucks’ emission, and energy consumption as well as sharing trucks among quay cranes and decreasing their empty trips. In this model trucks’ technical specifications and polluting levels are input parameters for estimating emission and energy consumption of operation, which consequently leads to two uniform parallel machine scheduling models. To derive the exact solution of the model, the epsilon-constraint method is applied. Nevertheless, due to the problem’s NP-hardness attribute, two variants of non-dominated sorting genetic algorithm and multiobjective particle swarm optimization metaheuristic algorithms are proposed to identify the approximate Pareto front of solutions. In large-size problems, these algorithms outperform the epsilon-constraint method by finding acceptable results in a reasonable time. This model, which could be embedded in terminal operating software, not only yields a practical optimum operational sequence but also measures the amount of energy and emission from trucks during loading and unloading operations. The results, which utilized the data collected from Shahid Rajaee port in southern Iran, indicate that this practical model as compared to the current procedure in the terminal, results in a significant improvement in energy and emission reduction and terminal flow time.