Search Results (316)

Background: Port congestion contributes significantly to operational inefficiency and environmental impact in maritime logistics. With tightening EU regulations such as the Emissions Trading System (EU ETS) and FuelEU Maritime, understanding and mitigating the economic and environmental effects of vessel delays is increasingly critical. This study focuses on a single bulk cargo pier at Constanta Port (Romania), which has experienced substantial traffic fluctuations since 2021, and examines operational and environmental performance through a queuing-theoretic lens. Methods: The authors have applied an M/G/1/∞/FIFO/∞ queuing model to vessel traffic and service time data from 2021–2023, supplemented by Monte Carlo simulations to capture variability in maneuvering and service durations. Environmental impact was quantified in CO₂ emissions using standard fuel-based emission factors, and a Cold Ironing scenario was modeled to assess potential mitigation benefits. Economic implications were estimated through operational cost modeling and conversion of CO₂ emissions into equivalent EU ETS carbon costs. Results: The analysis revealed high berth utilization rates across all years, with substantial variability in waiting times and queue lengths. Congestion was associated with considerable CO₂ emissions, which, when expressed in monetary terms under prevailing EU ETS prices, represent a significant financial burden. The Cold Ironing scenario demonstrated a substantial reduction in at-berth emissions and corresponding cost savings, underscoring its potential as a viable mitigation strategy. Conclusions: Results confirm that operational congestion at the studied berth imposes substantial environmental and financial burdens. The analysis supports targeted interventions such as Just-In-Time arrivals, optimized berth scheduling, and Cold Ironing adoption. Recommendations are most applicable to single-berth bulk cargo operations; future research should extend the approach to multi-berth configurations and incorporate additional operational constraints for broader generalizability. Full article

Background: The rapid growth of international maritime trade has intensified operational challenges at marine terminals due to increased interaction between vessels, trucks, and trains. Key issues include berth congestion, inefficient truck arrivals, and underutilization of terminal resources. Ensuring coordinated planning among transport modes and fostering collaboration between stakeholders such as vessel operators, logistics providers, and terminal managers is critical to mitigating these inefficiencies. Methods: This study proposes a multi-agent, multi-objective coordination model that synchronizes vessel berth allocation with truck appointment scheduling. A solution method combining prioritized planning with a neighborhood search heuristic is introduced to explore Pareto-optimal trade-offs. The performance of this approach is benchmarked against well-established multi-objective evolutionary algorithms (MOEAs), including NSGA-II and SPEA2. Results: Numerical experiments demonstrate that the proposed method generates a greater number of Pareto-optimal solutions and achieves higher hypervolume indicators compared to MOEAs. These results show improved balance among objectives such as minimizing vessel waiting times, reducing truck congestion, and optimizing terminal resource usage. Conclusions: By integrating berth allocation and truck scheduling through a transparent, multi-agent approach, this work provides decision-makers with better tools to evaluate trade-offs in port terminal operations. The proposed strategy supports more efficient, fair, and informed coordination in complex multimodal environments. Full article

The berth allocation and crane assignment problem (BACAP) is a key challenge in port logistics, particularly under dynamic and uncertain vessel arrival conditions. To address the limitations of existing methods in handling large-scale and high-disturbance scenarios, this paper proposes a novel optimization framework: Ternary Historical Memory-based Robust Clustered Particle Swarm Optimization (THM-RCPSO). In this method, the initial particle swarm is divided into multiple clusters, each conducting local searches to identify regional optima. These clusters then exchange information to iteratively refine the global best solution. A ternary historical memory mechanism further enhances the optimization by recording and comparing the best solutions from three different strategies, ensuring guidance from historical performance during exploration. Experimental evaluations on 25 dynamic BACAP benchmark instances show that THM-RCPSO achieves the lowest average vessel dwell time in 22 out of 25 cases, with the lowest overall average rank among five tested algorithms. Specifically, it demonstrates significant advantages on large-scale instances with 150 vessels, where it consistently outperforms competing methods such as HRBA, ACO, and GAMCS in both solution quality and robustness. These results confirm THM-RCPSO’s strong capability in solving dynamic and large-scale DBACAP scenarios with high disturbance levels. Full article

Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO₂ emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization. Full article

The port logistics service innovation (PLSI) is closely associated with cross-border e-commerce (CBEC) enterprise performance, given that the port, as the spatial carrier and the joint point of goods, information, customs house affairs, etc., is essentially a key node of the CBEC logistics chain. However, the influence mechanism of PLSI on CBEC enterprise performance has still not yet been elaborated by consensus. To fill this gap, this study aims to figure out the effect mechanism integrating the probe into two variables (i.e., information interaction and environmental upgrade) in a moderated mediation model. Specifically, this study collects questionnaire survey data of logistics enterprises and CBEC enterprises in the Ningbo-Zhoushan Port of China by the Bootstrap method in the software SPSS 26.0. The results show the following: (1) PLSI can positively affect the CBEC enterprise performance; (2) information interaction plays an intermediary role between PLSI and CBEC enterprise performance; and (3) environmental upgrade can not only positively regulate the relationship between information interaction and CBEC enterprise performance, but also enhance the mediating role of information interaction with a moderated intermediary effect. Full article

This study investigates how Chinese ownership in European ports affects trade flows between China and Eurozone countries, set against the backdrop of recent global economic disruptions that have emphasized the crucial role of maritime trade and port efficiency. An augmented gravity model was employed, using the Poisson pseudo-maximum likelihood (PPML), fixed effects (FE), and random effects (RE) estimators, to analyze trade data from 2001 to 2023. The analysis shows that, while conventional economic factors like GDP per capita and the Logistics Performance Index (LPI) consistently and significantly drive trade, Chinese port ownership surprisingly exhibits a negative or statistically insignificant impact on both Chinese exports to the EU and EU imports from China. This suggests that these acquisitions may not primarily boost overall bilateral trade but rather consolidate existing routes or serve broader strategic objectives, as evidenced by heterogeneous country-specific effects and phenomena like the “Rotterdam effect”. Ultimately, my findings underscore the paramount importance of logistical efficiency over ownership structure in facilitating trade. Full article

Short-sea shipping, abbreviated SSS, is the transportation of goods by sea over relatively short distances, in contrast to intercontinental ocean and deep-sea shipping. Short-sea shipping (SSS) is important for cargo transportation in some regions of the world with many ports and well-developed liner shipping. The development and improvement of SSS systems is an important scientific and practical task. This article presents theoretical and experimental results of the development and optimization of SSS. A methodology for connecting and evaluating SSS and other transport chains was developed and tested by experimental studies, with the help of which it is possible to assess the efficiency of SSS and other transport chains, e.g., in terms of economy, freight transportation time, and environmental impact. The developed SSS methodology includes sea and land transport corridors, their assessment, and possible ways of optimizing transport chains using a comparative method and can be applied to various transport and logistics chains. The basis for the development and verification of the SSS methodology was the theoretical and experimental results of real short-sea shipping operations. The use of a comparative method based on which transport and logistics chains are assessed allows one to search for the most optimal SSS routes and possible factors that allow optimizing transportation costs and reducing transportation time and environmental impact. Full article

Inefficient inland repositioning of empty containers between depots remains a persistent challenge in container logistics, contributing significantly to unnecessary truck movements, elevated operational costs, and increased CO₂ emissions. Acknowledging the importance of this problem, a large amount of relevant literature has appeared. The objective of this paper is to track the empty container flow between ports, empty depots, inland terminals, and customer premises. Additionally, it aims to simulate and assess CO₂ emissions, capturing the dynamic interactions between different agents. In this study, agent-based modeling (ABM) was proposed to simulate the empty container movements with an emphasis on inland transportation. ABM is an emerging approach that is increasingly used to simulate complex economic systems and artificial market behaviours. NetLogo was used to incorporate real-world geographic data and quantify CO₂ emissions based on truckload status and to evaluate the other operational aspects. Behavior Space was also utilized to systematically conduct multiple simulation experiments, varying parameters to analyze different scenarios. The results of the study show that customer demand frequency plays a crucial role in system efficiency, affecting container availability and logistical tension. Full article

Safe and efficient operation of port cranes is vital for maintaining the efficiency of global maritime logistics. However, traditional non-destructive testing methods face significant limitations in harsh port environments, such as periodic inspection intervals, restricted access to structural components, and a lack of real-time monitoring. This review explores the emerging paradigm of remote non-destructive testing through the integration of vibration and acoustic emission sensors with Internet of Things platforms. By enabling continuous, real-time monitoring, these sensor systems can detect early indicators of mechanical degradation, structural fatigue, and corrosion. This study synthesizes findings from over 100 peer-reviewed sources and identifies a significant gap in the application of these technologies to port cranes. Although vibration and acoustic emission sensors have been widely studied in various fields, their application to port cranes remains underexplored, presenting a novel and promising avenue for future research and practical applications. The unique operational demands and structural complexities of port cranes, coupled with their critical role in global trade logistics, make them ideal for leveraging these sensors in tandem with Internet of Things solutions. This integration not only overcomes the limitations of traditional non-destructive testing methods, but also offers substantial benefits, including enhanced safety, reduced inspection costs, and improved operational efficiency. This review concludes by proposing future research directions to enhance sensor performance, data analytics, and Internet of Things integration, paving the way for predictive maintenance strategies that increase operational uptime and improve safety in port crane operations. Full article

In the context of increasingly complex and dynamic maritime logistics, seaports serve as critical nodes for intermodal transport, energy distribution, and global trade. Ensuring the safe and uninterrupted operation of port infrastructure—particularly berths—is vital for maintaining supply chain resilience. This study explores the impact of multiple risk categories on berth efficiency in a seaport, aligning with the growing emphasis on maritime safety and risk-informed decision-making. A two-stage methodology is adopted. In the first phase, the DEA CCR input-oriented model is employed to assess the efficiency of selected berths considered as Decision Making Units (DMUs). In the second phase, the Analytical Hierarchy Process (AHP) is used to categorize and quantify the impact of four major risk classes—operational, technical, safety, and environmental—on berth efficiency. The results demonstrate that operational and safety risks contribute 63.91% of the composite weight in the AHP risk assessment hierarchy. These findings are highly relevant to contemporary efforts in maritime risk modeling, especially for individual ports and port systems with high berth utilization and vulnerability to system disruptions. The proposed integrated approach offers a scalable and replicable decision-support tool for port authorities, port operators, planners, and maritime safety stakeholders, enabling proactive risk mitigation, optimal utilization of available resources in a port, and improved berth performance. Its methodological design is appropriately suited to support further applications in port resilience frameworks and maritime safety strategies, being one of the bases for establishing collision avoidance strategies related to an individual port and/or port system, too. Full article

As a key node in port logistics systems, ship anchorage is often faced with congestion caused by ship flow fluctuations, multi-priority scheduling imbalances and the poor adaptability of scheduling models to complex environments. To solve the above problems, this paper constructs a ship scheduling algorithm based on a Markov-modulated fluid priority queue, which describes the stochastic evolution of the anchorage operation state via a continuous-time Markov chain and abstracts the arrival and service processes of ships into a continuous fluid input and output mechanism modulated by the state. The algorithm introduces a multi-priority service strategy to achieve the differentiated scheduling of different types of ships and improves the computational efficiency and scalability based on a matrix analysis method. Simulation results show that the proposed model reduces the average waiting time of ships by more than 90% compared with the M/G/1/1 and RL strategies and improves the utilization of anchorage resources by about 20% through dynamic service rate adjustment, showing significant advantages over traditional scheduling methods in multi-priority scenarios. Full article

This paper presents an enhanced hub location model tailored to port–hinterland logistics planning, grounded in the Capacitated Multiple-Allocation Hub Location Problem (CMAHLP). The formulation incorporates nonlinear cost structures, hub-specific operating costs, adaptive capacity constraints, and a feasibility condition based on the Social Net Present Value (NPVsocial) to support the design of intermodal freight networks under asymmetric spatial and socio-environmental conditions. The empirical case focuses on Spain, leveraging its strategic position between Asia, North Africa, and Europe. The model includes four major ports—Barcelona, Valencia, Málaga, and Algeciras—as intermodal gateways connected to the 47 provinces of peninsular Spain through calibrated cost matrices based on real distances and mode-specific road and rail costs. A Genetic Algorithm is applied to evaluate 120 scenarios, varying the number of active hubs (4, 6, 8, 10, 12), transshipment discounts (α = 0.2 and 1.0), and internal parameters. The most efficient configuration involved 300 generations, 150 individuals, a crossover rate of 0.85, and a mutation rate of 0.40. The algorithm integrates guided mutation, elitist reinsertion, and local search on the top 15% of individuals. Results confirm the central role of Madrid, Valencia, and Barcelona, frequently accompanied by high-performance inland hubs such as Málaga, Córdoba, Jaén, Palencia, León, and Zaragoza. Cities with active ports such as Cartagena, Seville, and Alicante appear in several of the most efficient network configurations. Their recurring presence underscores the strategic role of inland hubs located near seaports in supporting logistical cohesion and operational resilience across the system. The COVID-19 crisis, the Suez Canal incident, and the persistent tensions in the Red Sea have made clear the fragility of traditional freight corridors linking Asia and Europe. These shocks have brought renewed strategic attention to southern Spain—particularly the Mediterranean and Andalusian axes—as viable alternatives that offer both geographic and intermodal advantages. In this evolving context, the contribution of southern hubs gains further support through strong system-wide performance indicators such as entropy, cluster diversity, and Pareto efficiency, which allow for the assessment of spatial balance, structural robustness, and optimal trade-offs in intermodal freight planning. Southern hubs, particularly in coordination with North African partners, are poised to gain prominence in an emerging Euro–Maghreb logistics interface that demands a territorial balance and resilient port–hinterland integration. Full article

This study proposes a balanced truck dispatching strategy for inter-terminal transportation (ITT) in large ports, incorporating proactive demand outsourcing to address stochastic and imbalanced ITT demand. A portion of ITT tasks are intentionally outsourced to third-party public trucks at a higher cost, so that self-owned trucks can be reserved for more critical tasks. The ITT system is modeled as a closed Jackson network, in which self-owned trucks circulate among terminals and routes. An optimization model is developed to determine the optimal proactive outsourcing ratios for origin–destination terminal pairs and the appropriate fleet size of self-owned trucks, aiming to minimize total transportation costs. Reactive outsourcing is also included to handle occasional truck shortages. A mean value analysis method is used to evaluate system performance with given decisions, and a differential evolution algorithm is employed for optimization. The case study of Shanghai Yangshan Port demonstrates that the proposed strategy reduces total system cost by 9.8% compared to reactive outsourcing. The results also highlight the importance of jointly optimizing outsourcing decisions and fleet size. This study provides theoretical insights and practical guidance for ITT system management under demand uncertainty. Full article

Based on a comprehensive evaluation index system for regional economic resilience and port logistics development, this study employs multiple methodologies including coupling coordination degree model, kernel density estimation, gravity center model, spatial autocorrelation model, and geographic detector model to explore the spatial–temporal evolution patterns and driving factors of coupling coordination between regional economic resilience and port logistics in the Guangxi Beibu Gulf Economic Zone from 2012 to 2022. The results indicate that: (1) The coupling coordination degree between the two systems showed an upward trend during the study period, although with stage-specific bipolar differentiation that weakened in the later stages. (2) The spatial distribution pattern of coupling coordination evolved from a “single-core” driven by Nanning to a “dual-core” led by Nanning and Yulin, forming a distinct concentric layer structure; the gravity center of coupling coordination exhibited a “southeast–northwest” dynamic migration pattern. (3) Spatial autocorrelation analysis revealed significant positive spatial dependence of coupling coordination within the study area, with spatial agglomeration values showing a “core–transition–depression” differentiation pattern. (4) Information technology level emerged as the dominant driving factor, forming a “technology–finance–infrastructure” ternary collaborative driving model with financial development level and logistics infrastructure level, which became the main force promoting the coordinated development of the coupled systems. Full article

The global port and maritime industry is experiencing a new paradigm shift known as the artificial intelligence transformation (AX). Thus, domestic container-terminal companies should focus beyond mere automation to a paradigm shift in AI that encompasses operational strategy, organizational structure, system, and human resource management. This study proposes a resilience-based AX strategy and implementation system that allows domestic container-terminal companies to proactively respond to the upcoming changes in the global supply chain, thus securing sustainable competitiveness. In particular, we aim to design an AI-based governance model to establish a trust-based logistics supply chain (trust value chain). As a research method, the core risk factors of AX processes were scientifically identified via text-mining and fault-tree analysis, and a step-by-step execution strategy was established by applying a backcasting technique based on scenario planning. Additionally, by integrating social control theory with new governance theory, we designed a flexible, adaptable, and resilience-oriented AI governance system. The results of this study suggest that the AI paradigm shift should be promoted by enhancing the risk resilience, trust, and recovery of organizations. By suggesting AX strategies and policy as well as institutional improvement directions that embed resilience to secure the sustainable competitiveness of AI-based smart ports in Korea, this study serves as a basis for establishing strategies for the domestic container-terminal industry and for constructing a global leading model. Full article