Explore the vast range of titles available.

Increasing freight volumes and challenging environments in seaports and container terminals worldwide require streamlined and reliable operations. Digital twins are seen as important drivers of the digitalization in seaports by providing a basis for higher transparency, control and data-driven decision making. In this context, however, the concept is rarely studied, and implementation issues are not comprehensively discussed. The paper presents an exploratory study of digital twins in seaports based on a literature review and case studies. The analysis reveals a standardization deficit for digital twin implementations, an inflationary and improper use of the term digital twin, and fields of research that need to be explored further. The application of optimization methods and the integration of simulation-based optimization in the field of seaports and container terminals is examined, due to its relevance for digital twins. Important lessons learned can be taken from the most advanced implementations, integrating simulations and emulations with optimization methods. An in-depth examination of multiple case studies and discussions with global port leaders yields valuable perspectives on the varied levels of digital twin implementations being applied today, including insights into the most advanced implementations currently being used in ports and container terminals. As a result of the analyses conducted, various research directions and a research agenda are presented.

This paper studies the daily storage yard manage problem arising in maritime container terminals, which integrates the space allocation and yard crane deployment decisions together with the consideration of container traffic congestion in the storage yard. The integrated problem is formulated as an integer linear programming model with the objective of minimizing the yard crane operating cost and the yard crane interblock movement cost. A divide-and-conquer solution approach is designed to solve the problem in an efficient manner in which harmony search and constraint satisfaction techniques are employed. Numerical experiments are conducted to validate the performance of the solution approach and the improvement from the integrated optimization method.

Operations research techniques have helped optimize container terminal operations over the past decades and have been a regular feature of maritime logistics and maritime supply chain literature in addition to being in practice at container terminals across the globe. Our systematic review collated through Scopus, 1768 papers published in the domain and analyzed them to find the main research clusters, and explore future research directions. Studies on both quayside and landside planning are grouped in five research clusters: discussing simulation, scheduling, automation, quayside operations, integrated operations and container transportation. In addition, the evolution of optimization techniques in planning container terminal operations is discussed, along with the suggested trajectory of the research agenda under each cluster. The analysis finds that genetic algorithms, integer linear programming and heuristics are the most widely used operations research techniques in container terminal optimization. While clusters of research in areas such as simulating container terminal operations, scheduling operations and automated terminals have received a great deal of attention, research focusing on integrated and dynamic operations has been scarce over the past years, suggesting a new area of contributions. The review proposes the application of methods such as neural network- and deep learning models related to artificial intelligence to widen our understanding of container terminal operations.

Ship emissions in and around ports are of interest for urban air quality management in many harbour cities. We investigated the impact of regional and local ship emissions on urban air quality for 2012 conditions in the city of Gothenburg, Sweden, the largest cargo port in Scandinavia. In order to assess the effects of ship emissions, a coupled regional- and local-scale model system has been set up using ship emissions in the Baltic Sea and the North Sea as well as in and around the port of Gothenburg. Ship emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM), taking into account individual vessel characteristics and vessel activity data. The calculated contributions from local and regional shipping to local air pollution in Gothenburg were found to be substantial, especially in areas around the city ports. The relative contribution from local shipping to annual mean NO2 concentrations was 14 % as the model domain average, while the relative contribution from regional shipping in the North Sea and the Baltic Sea was 26 %. In an area close to the city terminals, the contribution of NO2 from local shipping (33 %) was higher than that of road traffic (28 %), which indicates the importance of controlling local shipping emissions. Local shipping emissions of NOx led to a decrease in the summer mean O3 levels in the city by 0.5 ppb (∼2 %) on average. Regional shipping led to a slight increase in O3 concentrations; however, the overall effect of regional and the local shipping together was a small decrease in the summer mean O3 concentrations in the city. In addition, volatile organic compound (VOC) emissions from local shipping compensate up to 4 ppb of the decrease in summer O3 concentrations due to the NO titration effect. For particulate matter with a median aerodynamic diameter less than or equal to 2.5 µm (PM2.5), local ship emissions contributed only 3 % to the annual mean in the model domain, while regional shipping under 2012 conditions was a larger contributor, with an annual mean contribution of 11 % of the city domain average. Based on the modelled local and regional shipping contributions, the health effects of PM2.5, NO2 and ozone were assessed using the ALPHA-RiskPoll (ARP) model. An effect of the shipping-associated PM2.5 exposure in the modelled area was a mean decrease in the life expectancy by 0.015 years per person. The relative contribution of local shipping to the impact of total PM2.5 was 2.2 %, which can be compared to the 5.3 % contribution from local road traffic. The relative contribution of the regional shipping was 10.3 %. The mortalities due to the exposure to NO2 associated with shipping were calculated to be 2.6 premature deaths yr−1. The relative contribution of local and regional shipping to the total exposure to NO2 in the reference simulation was 14 % and 21 %, respectively. The shipping-related ozone exposures were due to the NO titration effect leading to a negative number of premature deaths. Our study shows that overall health impacts of regional shipping can be more significant than those of local shipping, emphasizing that abatement policy options on city-scale air pollution require close cooperation across governance levels. Our findings indicate that the strengthened Sulphur Emission Control Areas (SECAs) fuel sulphur limit from 1 % to 0.1 % in 2015, leading to a strong decrease in the formation of secondary particulate matter on a regional scale was an important step in improving the air quality in the city.

The ever increasing demand for container transportation has led to the congestion of maritime container terminals in the world. In this work, the two interrelated problems of berth and quay crane scheduling are considered in an integrated multiobjective mathematical model. A special character of this model is that the arrival times of vessels and the failure (working) times of quay cranes are not deterministic and can vary based on some scenarios. Hence, a robust model is devised for the problem having three objectives of minimising the deviations from target berthing locations and times as well as departure delays of all vessels. This robust optimisation seeks to minimise the value of the objectives regarding all the scenarios. An exact solution approach based on the 𝜖 -constraint method by the Gurobi software is applied. Moreover, regarding the complexity of the problem, two Simulated Annealing (SA) based metaheuristics, namely a Multi-Objective Simulated Annealing (MOSA) and a Pareto Simulated Annealing (PSA) approach are adapted with a novel solution encoding scheme. The three methods are compared based on some multiobjective metrics and a statistical test. The advantage of the integration of berth and quay crane scheduling is examined as well.

Climate change and global warming along with human activities have caused abrupt changes in the atmosphere, marine, and terrestrial ecosystems. One of these changes is the rising number of mucilage events in marine ecosystems. During the recent two decades, mucilage blooms have begun to appear more frequently in the Sea of Marmara in Turkey, surrounded by seven densely populated cities with various anthropogenic activities including household pollution, heavy industrialization, agricultural pollution, commercial fishing, shipyards, and specialized marine terminals with high maritime traffic density. In Spring 2021, a massive mucilage event observed in the Sea of Marmara plagued the entire ecosystem and raised awareness among the government and the public to detect and monitor this phenomenon. In this research, daily monitoring and detection of mucilage formations from the coarse spatial resolution MODIS products were investigated during the 2021 bloom period. The results were validated with the reference mucilage datasets derived from Sentinel-2A imagery and in situ spectroradiometer measurements over mucilage formations. The results revealed that the MODIS surface reflectance profiles were highly correlated with the field spectral measurements and estimated mucilage formations were spatially overlapped with Sentinel-2A. Overall, the produced maps accurately depicted the mucilage-covered areas despite the limitations of unreliable estimates along the land–water transition lines, and no-data areas due to the low-quality observations and high cloud coverage.

Increasing international maritime transport drives the need for efficient container terminals. The speed at which containers can be processed through a terminal is an important performance indicator. In particular, the productivity of the quay cranes (QCs) determines the performance of a container terminal; hence QC scheduling has received considerable attention. This article develops a comprehensive model to represent the waterside operations of a container terminal. Waterside operations comprise single and twinlift handling of containers by QCs, automated guided vehicles and yard cranes. In common practice, an uncoordinated scheduling heuristic is used to dispatch the equipment operating on a terminal. Here, uncoordinated means that the different machines that operate in the container terminal seek optimal productivity solely considering their own respective stage. By contrast, our model provides a coordinated schedule in which operations of all terminal equipment can be considered at once to achieve productivity closer to the QC optimal. The model takes the form of a hybrid flow shop (HFS) with novel features for bi-directional flows and job pairing. The former enables jobs to move freely through the HFS in both directions; the latter constrains certain jobs to be performed simultaneously by a single machine. We solve the coordinated model by means of a tailored simulated annealing (SA) algorithm that balances solution quality and computational time. We empirically study time-bounded variants of SA and compare them with a branch-and-bound algorithm. We show that our approach can produce coordinated schedules for a terminal with up to eight QCs in near real time.

The introduction of ever-larger containerships is a much-discussed topic in academic and business circles. The largest containership size has evolved from about 5500 TEU in 1995 to more than 23,000 TEU in 2019. The economic rationale for further scale increases in ship size is largely dependent on the current and future market conditions in the container shipping market, the adaptive capacity of ports and terminals (both economically and technologically) and, more recently, environmental requirements and considerations. This paper evaluates under which economic, operational and environmental conditions and expectations, shipping companies are likely to push the ultra-large containership (ULCS) size from 18,000 to 20,000 TEU to 25,000 TEU. Differences in both annual container slot cost and more comprehensive cost–benefit measures are assessed under different key market-based and operational conditions. The basic cost parameters for 20,000 TEU and 25,000 TEU vessels were estimated using a regression analysis applied to actual data of vessels up to 18,000 TEU. Our findings show that a further scale increase to a 25,000 TEU ULCS still generates economies of scale. However, very low freight rates, i.e. even below the poor freight rates of 2016–2017, and low load factors would not be conducive to the economic viability of 25,000 TEU ships, compared to smaller ULCSs. This study complements and updates the findings of previous studies (which focused on much smaller ship sizes) and contributes to the ongoing academic and corporate discussion on drivers and impediments of scale increases in vessel size by explicitly incorporating time- and context-dependent factors affecting optimal ship size.

Atmospheric pollutants from container terminal operations have adverse effects on the environment in port regions, leading to increased health risks, including respiratory and cardiovascular diseases among local residents. This paper aims to assess bio-efficiency for container terminals (CTs) in the presence of air emissions utilizing a slacks-based measure (SBM) model. In doing so, the paper first adopts cluster analysis to elect homogeneous CTs that aligns with the assumption of DEA theory, then uses a new method to estimate air emissions generated by CTs’ operations at harbor zones. Next, the SBM model is used to estimate the bio-efficiency of CTs in the presence of air emissions. Finally, CTs in the Ba Ria-Vung Tau port authorities (PAs) are employed as an empirical study to verify the proposed research model. The proposed research framework can contribute a methodological reference towards the relevant literature on abating atmospheric pollutants in maritime regions.

Purpose In Industry 4.0 era, many existing port logistics systems are inconsistent, old and ineffective and it restricts the effective operations of port logistics. The study aims to understand the issues faced by the players/actors of port logistics in the Industry 4.0 era for emerging economies and to develop a conceptual framework for managing the port logistics issues associated with it and by providing their possible solutions.Design/methodology/approach The study is divided into two parts, first part deals with identifying the major port logistics issues in Industry 4.0 era for emerging economies. It is achieved by conducting a semi-structured interview during the field visit to one of the major container handling ports in India. Second, the study adopts Soft System Methodology (SSM) to understand the issues and challenges faced by various actors of port logistics in the Industry 4.0 era and uses CATWOE analysis to identify the root causes.Findings Issues related to loading/unloading, transit, storage (warehouse), customs clearance, regulatory authorities, port management unit and inland transport connection providers are considered in the study and using SSM a final implementable model has been developed. This study focuses on analyzing and understanding the complete communication and organization structure of the port logistics system. The study identifies the major issues, various inefficiencies and root causes faced by various actors of port logistics during information sharing, cargo movement, the arrangement of the cargo shipments, etc. Further, the study develops a final implementable model by combining the delivery system, criteria system and Industry 4.0-enabled system.Research limitations/implications The study enables concerned authorities like state government, central government and policymakers to have a profound understanding of the issues faced by the actors of the port logistics system. The study brings out valuable insights that help managers and stakeholders to make informed decisions for managing the port logistics issues and develop necessary policies aimed to deliver the cargoes in right place at right time. The current study also has some limitations because of sensitivity associated with concerned areas, due to its confidentiality, lack of availability of complete data and the nonsharing attitude of respondents. Further, the study was conducted only for private container shipping terminals and public container terminals were not included.Originality/value This research analyzes the port logistics sector as a whole system through SSM to identify issues and challenges faced by various actors of port logistics for emerging economies in the Industry 4.0 era. The study develops a comprehensive and integrated framework for reducing the unpredictability of costs and time for key processes. Further, the framework creates a transparent platform and helps in bringing standardization to ports.