Port Operations Research Articles

Connected and automated vehicle loading system for improving operational inefficiency from human driven vehicle in roll-on/roll-off port operations

ABSTRACT This study aims to identify the non-value-adding activities during vehicle stowage operations in automobile terminals and propose a connected automated vehicle (CAV) loading system, a self-driving-car-loading system. Furthermore, the productivity of the CAV loading system is compared with the current loading system. A simulation model of an actual loading system was developed using the software FlexSim. The simulation results showed that the walking time of workers, operation time of shuttle vans, and waiting time occupied a large part of the cycle time in the current operation system. The proposed CAV loading system has eliminated these inefficiencies, and increased productivity by 26.78%. This is the first study to (1) present a self-driving-car-loading system in a simulated automobile terminal of a real-world size, and (2) propose a CAV loading system. Results provide useful insights for the integration of self-driving technology into future automobile port operations.

Risk evaluation for oil tanker berthing and handling operations using the improved DEMATEL-ISM approach

The berthing and handling operation of oil tankers is an important task in the operation of oil ports. Therefore, it is crucial to identify the risk factors in the process of the berthing and handling operation of oil tankers, to explore the relationship between the influencing factors of the risk, and to find out the key factors that incur risk. In this paper, the risk factors of oil tankers’ berthing and handling operations are identified through on-site investigation, interviews, questionnaire surveys and expert consultation. Aiming at the uncertainty of the weight of each risk index during oil tanker berthing and handling, a machine learning algorithm (i.e. Random Forest Weighting) is applied. In this sense, the reliability analysis is used to calculate the generalization error of expert scoring data, and the weight of each index of each evaluation item is obtained according to the minimum error rate, which reduces the impact of subjective weighting in the identification of cause-effect chain components. In order to examine the internal relationship among various factors, the Interpretive Structural Model (ISM) of risk factors is constructed. Furthermore, we analyse the hierarchical relationship between various factors, clarify the mechanism of risk generation, and propose strategies to improve the safety management level of oil tanker terminals. Results show that the used algorithm could identify the key risk factors in the risk oil tanker terminal operations, and provide more effective managerial recommendations.

Managing noise from port operations via the use of automated noise monitoring systems

Ports are key pieces of infrastructure that enable the transportation of goods and passengers. Bays Port, Sydney NSW is located in close proximity to communities and balances the increased demand for Port facilities and services with community expectations, environmental requirements and regulatory approvals. For noise generated from Port activities at Bays Port, historically, individual port users have been required to monitor and evaluate noise under different environmental requirements and planning approvals, which can lead to inconsistent reporting, noise limits and regulation between operators and a lack of clarity for the community. Port Authority of NSW has implemented a first of its kind policy in Australia for the management of Port noise from both individual vessel and landside noise sources. To achieve these objectives, an automated directional noise monitoring system has been implemented to provide real-time measurement and analysis of noise contributions from vessel and landside activities. The system utilizes live data of individual vessel tracking locations, meteorology and an array of 6 direction microphones located around the port infrastructure. This information feeds into a live platform to facilitate management of port noise operations. This paper provides an overview of the Port Noise Policy and the use of unattended directional noise monitoring systems to meet the policy’s aims. Case studies are also provided to illustrate the benefits of real time monitoring systems in pro-actively managing port noise.

Measurements of ship noise using an acoustic camera: A first survey

While the acoustic impact of harbors is becoming an increasingly important issue, to the point of limiting their growth, the measurement of noise from ships and port operations is still rough. Two of the main problems that are commonly encountered are source overlapping and large distance from the emitting sources. Source overlapping prevents from identifying the specific contribution coming from each acoustic source. The large distance from the emitting sources, for instance the funnel of a ship or the engine of a transtainer crane, makes the measurement inaccurate. By using the acoustic camera, it is possible to tackle these two problems at the same time. Noise measurements can be made with equipment far from noise source, while distinguishing the contribution from each single source emitting within the sound field. The paper demonstrates this enhanced measurement technique through a set of surveys performed inside French and Italian ports. The ship emissions are analyzed through the acoustic camera for ship on the way, maneuvering inside the harbor, and berthed at wharf. The effectiveness of beamforming technique is discussed, investigating the measurements accuracy, their qualitative and quantitative significance, and the possibility to introduce specific measurement standards for ships based on this methodology.

Impact of Coastal Reclamation on Seagrass Habitat in Palu Bay, Central Sulawesi, Indonesia

Coastal development by conducting reclamation for various uses, for example port construction and operations, is a growing threat to coastal ecosystems including seagrass meadows. For several decades, reclamation for coastal development in Palu Bay has included port construction or extension of single-purpose privately owned port facilities as well as public shipping ports. In addition, reclamation was carried out to provide land for the construction of hotels, housing, recreational areas and coastal protection. The majority of private port terminals are owned by mining companies exporting rock and aggregate from around Palu Bay. There are many quarries in the mountains along the western coast of Palu Bay, and alluvial materials around several rivers along the eastern shore are also exploited. The purpose of this study was to analyse the impact of reclamation on seagrass habitat in Palu Bay, especially the private ports, which the dominant reclamation purposes conducted in this area. This study found about 66 ports around Palu Bay, the majority privately owned by mining companies operating in Palu City and Donggala Regency. The effects of reclamation include reduced seagrass habitat and decreased water quality.

УПРАВЛІННЯ ЛАНЦЮГАМИ ПОСТАЧАНЬ В КОНТЕКСТІ ДЕСТАБІЛІЗАЦІЇ БІЗНЕС-СЕРЕДОВИЩА

The article is devoted to the study of issues related to the management of supply chains in the conditions of destabilization of the business environment during the martial law in Ukraine. In particular, the impact of the war in Ukraine on modern international supply chains and the reasons for the increase in transportation costs are analyzed. It is emphasized that the war in Ukraine due to the Russian attack led to the destruction and damage of the transport and logistics infrastructure the suspension of port operations in Ukraine, which in turn affected the efficiency of supply chains, changes in logistics routes, and as a result, the prices of goods and services. Attention is focused on the fact that the supply chain combines a set of different types of activities and is a complex business process in the combination of manufacturers and retailers at each stage of the distribution process from raw materials to delivery to the final consumer. It has been proven that the first disruptions in supply chains occurred due to the coronavirus pandemic, but military actions also had an additional impact, which ultimately created some uncertainty in the management of global supply chains and their inefficiencies. Four groups of key performance indicators of the supply chain are distinguished, namely, those related to the logistics product; with the search for information and financial sources; with transportation and pricing. It is proposed that the key performance indicators of the supply chain should be taken into account when forming a business strategy for the development of an enterprise in the context of a destabilizing environment, which will ensure success in the future. In the formation and management of supply chains, the most acute problem is uncertainty, which creates unpredictability of risks, complicates the process of their identification, assessment, development of a risk management strategy and monitoring. To support the reliability and stability of supply chains, a generalized scheme of risk management in supply chains has been developed. The implementation of such a scheme allows you to reduce risks, operational costs, increase key performance indicators of the supply chain, adhere to the environmental friendliness of business processes, and improve the level of customer service in conditions of destabilization of the business environment.

AN INVESTIGATION OF THE UTILISATION OF ENGLISH IN THE INTERNSHIP PROGRAMS AMONG THE CADETS OF NUSANTARA MARITIME ACADEMY

This study aims to examine the utilisation of the English language within the context of the internship programme for maritime cadets, utilising interviews and observations as primary data collection methods. This qualitative research endeavour seeks to offer valuable insights into the role of English language in the internship program for maritime professionals. The findings of this study have made significant contributions to the improvement of language training programmes, communication protocols, and overall safety and efficiency in maritime internship settings. The empirical evidence indicates that possessing a strong command of English is essential for successfully carrying out safety drills, ensuring smooth vessel navigation and engine maintenance, fostering intercultural comprehension and efficient collaboration, and overseeing documentation procedures in port operations. The study places significant emphasis on the necessity of efficient language instruction, the resolution of language-related obstacles, and the facilitation of intercultural dialogue in order to adequately equip maritime academies and internship programs for fruitful internships and prospective careers as skilled and capable seafarers.

코로나19 전후 항만 효율성 분석에 관한 연구

Since COVID-19, congestion has become an important factor that can hinder the efficient operation of ports and cause direct and indirect economic damages. Therefore, this study conducted an SBM-DEA analysis with congestion as a undesirable output variable to investigate the impact of congestion on the efficiency of four Korean ports (Busan, Yeosu-Gwangyang, Ulsan, and Incheon) before and after COVID-19. The analysis revealed that the overall efficiency of the ports was lower after the outbreak of COVID-19 than before, and that the efficiency of each port was relatively different depending on its infrastructure and budget. This analysis shows that port efficiency is being negatively affected by congestion both pre- and post- COVID-19. Additionally, port infrastructure and budgets have a direct impact on congestion levels. To enhance port efficiency, it's important to implement appropriate systems and policies to manage congestion while considering the unique characteristics of each port.

An improved deep reinforcement learning approach: A case study for optimisation of berth and yard scheduling for bulk cargo terminal

The cornerstone of port production operations is ship handling, necessitating judicious allocation of diverse production resources to enhance the efficiency of loading and unloading operations. This paper introduces an optimisation method based on deep reinforcement learning to schedule berths and yards at a bulk cargo terminal. A Markov Decision Process model is formulated by analysing scheduling processes and unloading operations in bulk port imports business. The study presents an enhanced reinforcement learning algorithm called PS-D3QN (Prioritised Experience Replay and Softmax strategy-based Dueling Double Deep Q-Network), amalgamating the strengths of the Double DQN and Dueling DQN algorithms. The proposed solution is evaluated using actual port data and benchmarked against the other two algorithms mentioned in this paper. The numerical experiments and comparative analysis substantiate that the PS-D3QN algorithm significantly enhances the efficiency of berth and yard scheduling in bulk terminals, reduces the cost of port operation, and eliminates errors associated with manual scheduling. The algorithm presented in this paper can be tailored to address scheduling issues in the fields of production and manufacturing with suitable adjustments, including problems like the job shop scheduling problem and its extensions.

Operational adaptation of ports with maritime autonomous surface ships

Preliminary research findings suggest that the successful integration of advanced autonomous technologies in cargo ships could provide safer shipping and provide economical benefits. However, the fact that ships can sail with the assistance of autonomous technologies is not sufficient evidence alone to comprehend the promises of autonomous systems for maritime transport operations. Simultaneously, the entire global maritime transport system must also adapt to the advanced autonomous technologies and act interoperable with ships. In this context, this study aims to examine the areas of interoperability requirements with ports for the effective and integrated operation of autonomous cargo ships. In accordance with the purpose of the study, the operational context in which ships and ports interact is determined, and their interoperability in an autonomous maritime transport scenario is analysed. The present study contains the application of a survey questionnaire reflecting the views of experts dealing with ship and port operations. The data collected by the survey questionnaire are analysed by applying multiple regression analysis methods, utilising the IBM SPSS program. This study is in a pioneer position to define the interoperability characteristics to improve port operations to work in harmony with autonomous ships. The findings of this research are anticipated to contribute significantly to shaping the future of smart and autonomous freight transport and logistics.

Enhancing Maritime Safety and Efficiency: A Comprehensive Sea Fog Monitoring System for Ningbo Zhoushan Port

Sea fog poses a considerable challenge to port operations, impacting maritime safety and efficiency. During the past five years, the average annual downtime of the navigation dispatch department in Ningbo Zhoushan Port due to weather was 800–1000 h, of which approximately 300 h can be attributed to sea fog. This study addresses the issue by developing a comprehensive sea fog monitoring system for Ningbo Zhoushan Port. The system utilizes automatic weather stations (AWS) and visibility laser imaging, detection, and ranging (LIDAR) to assess sea fog severity and improve monitoring accuracy. By increasing monitoring frequency and adopting corresponding warning measures, the system aims to enhance maritime safety and efficiency in Ningbo Zhoushan Port. The results showed that the implemented system successfully determines sea fog severity, enables real-time monitoring, and provides precise visibility assessments. Joint assessments revealed a substantial increase in the annual operating time and revenue of the port. These findings underscore the importance of advanced monitoring techniques in optimizing port operations, reducing collision risks, and mitigating economic losses caused by sea fog.

Green port management practices for sustainable port operations: a multi method study of Asian ports

ABSTRACT Ports pose a substantial portion of marine emissions, causing significant health and environmental risks. Providing profitable services in compliance with environmental regulations has become a significant challenge for port authorities. The idea of green port management practices (GPMP) has recently grown as an innovative method for balancing port economic growth with ecological issues. The study systematically reviewed the literature regarding the green port management model and identified an integrated set of drivers of GPMP for sustainable port operations. Besides, an empirical multiple case study methodology was adopted where twelve major Asian ports from developing and developed countries were investigated through a performance-based scoring measurement method based on their GPMP drivers’ implementation status. Finally, the study employed a quantitative fuzzy decision-making trial and evaluation laboratory model (DEMATEL) to examine the interdependent cause-and-effect connections among the different green port drivers. The study reveals that Singapore is rated highest in green port implementation practices while the Port of Male (Maldives) was classified lowest among 12 Asian ports. Besides, Pollution Control Measures are the most significant driver having the highest influence on all drivers. Automation and digitalization have the most significant causal influence on all the drivers of GPMP, followed by environmental incentives and penalty pricing.

Evaluation of port competitiveness along China’s “Belt and Road” based on the entropy-TOPSIS method

Based on the literature on the factors influencing port competitiveness, this paper evaluates the competitiveness of Chinese ports along the Belt and Road based on Porter’s diamond model. The evaluation system includes four primary indicators, including port infrastructure, port operation scale, port hinterland economic level and port development potential, and 13 secondary indicators. Then, based on the entropy-TOPSIS method, an evaluation model of port competitiveness is constructed. Finally, 15 seaports along China’s “Belt and Road” are used to evaluate competitiveness, and a comprehensive ranking of port competitiveness is obtained. The advantages and shortcomings of each port are pointed out according to the evaluation results to provide a reference for the long-term development of the competitiveness of ports along the “Belt and Road” in China.

Cloud-based system for monitoring loads generated on the quay wall by ship propeller jets

The paper presents a cloud-based system for monitoring loads generated on the quay wall by ship propeller jets during berthing and unberthing maneuvers. The system provides online measurements of the dynamic pressure generated loads by propellers and warns of exceeding the permissible jet velocities over the seabed protection along the berth. The system has a modular structure consisting of a network of pressure sensors, information mapping server, communication module and web server. The suitability of the system was confirmed during two years of operation in Port of Gdynia. The open architecture of the system allows for its further extension with additional berths and integration with the smart port system.

An alternative solution to congestion relief of U.S. seaports by container-on-barge: A simulation study

Port congestion has become a big challenge for many seaports in the United States (U.S.). There are multiple factors contributing to port congestion, such as the booming market of international container trading, limited space and capacity at a seaport, labor shortages, equipment failures, and supply chain disruptions (e.g., COVID-19 pandemic). Without appropriate management, port congestion will increase transportation costs, cause delays in goods movement and cargo delivery, reduce port operation efficiency, and lead to supply chain disruptions. Traditional strategies, such as infrastructure investment, truck appointments optimization, and party cooperation enhancement, have been implemented by ports for years, but the results are often unsatisfactory. To learn the needs of U.S. seaports and seek an efficient method for congestion relief, we develop a discrete event simulation model incorporating Container-on-Barge (COB) as an alternative transportation mode in this study. The simulation model mimics port operations involving COB and investigates congestion times at berth, yard, and gates. A case study on the Port of New Orleans (Port NOLA) is conducted to demonstrate the implementation of the simulation model and to evaluate the potential of COB for seaport congestion relief. The simulation results suggest that with a good level of COB development, the congestion at berth, yard and entrances of a seaport can be decreased significantly.

Optimal design of an adaptive energy management strategy for a fuel cell tractor operating in ports

As World trade is growing rapidly, the reduction of the environmental impact of in-port operations towards a low or zero-emission scenario is becoming a paramount issue. To this aim, replacing Diesel engines of cargo handling equipment used in port logistics (e.g. reach stackers, forklifts, yard tractors, etc.) with cleaner propulsion alternatives may play a major role. In this study, a robust rule-based energy management strategy is proposed for a newly developed fuel cell/battery hybrid powertrain of a yard tractor used for roll-on and roll-off in-port operations. As typical port operations are characterized by mission profiles that can vary significantly in terms of driving and duty cycles during the same work-shift, the proposed strategy, built upon the observation of the powertrain behavior under the application of an optimal controller, dynamically adapts the operation of fuel cell and battery in order to track a predefined battery state of charge trajectory, while minimizing the hydrogen consumption. The use of an optimal model-based approach as a reference for the design of an online implementable energy management strategy is indeed particularly suitable in the present case: despite their inherent high variability, the yard tractor mission profiles can be regarded as the combination of a set of predictable parameters. Results show that the application of the proposed control strategy allows the hybrid powertrain to achieve excellent performance, by leading its components to run efficiently and across suitable operative conditions. The achieved hydrogen consumption, for the considered missions, is only 2%–3% higher than that of the optimal controller, despite a quite different evolution of the battery state of charge, that is the feedback control variable. By means of this strategy, the transient loading of the fuel cell is prevented, while the battery pack ensures the fulfillment of the peak power requests, with beneficial effects in terms of on-board stored energy exploitation. The key advantage of the developed rule-based approach lies in its robustness, reliability and online applicability in real-time powertrain control.

Contemporary challenges and AI solutions in port operations: applying Gale–Shapley algorithm to find best matches

Artificial intelligence (AI) developments enable human capability to deliver the same outcome at a lower cost. This research performs a high-level matching between AI solutions and challenges within the port area by developing a novel academic approach. This way, the matching is carried out more structured than when one (manager, developer, challenge owner, etc.) fulfils it based on their opinion without following any structured approach. Therefore, the study defines first a comprehensive typology of port stakeholders' challenges, which can be solved via AI solutions. This typology presents challenges, including their main issues, widespread impact, and potential solutions. A state-of-the-art review of AI solutions that can address these challenges is carried out in parallel. Secondly, this review clearly distinguishes between AI solutions based on their technology and functionality. Thirdly, this research selects an appropriate AI solution for addressing each identified challenge in the port operation by upgrading the Gale–Shapley algorithm. Finally, it shows that the most critical presented AI solutions in this study use various machine learning (ML) techniques. Besides, concerning the AI solution's reusability feature and the result of high-level matching, this research shows that the implementation phase effort can be drastically reduced by using the recently developed matching algorithm.

Efficient Container Logistics System Model

The containers were associated with import-export businesses via sea transport. It had an impact on economic value and was essential for logistics development. The Overseas Container Management System literature review found numerous papers that tend upward in port operations, container yards, or container terminals. This study follows this trend and is driven to learn about processes and container management systems in container yards. The research aims to study container management system analysis and the factors influencing an efficient container yard management system. This research is applied research, which includes collecting relevant documents, actual field data, surveys, and observation techniques. The sampling frame consisted of 400 trucks in a specific case study of an empty container terminal operation area in Bangkok port (Cargo Operations Division 3). Data was collected by the Case Record/Report Form (CRF). Binary logistic regression was used to analyze the relationship between the independent factors and the dependent variable. Keywords: Container, Empty Container Terminal, Container Yard, Container Management System

Port Digital Twin Development for Decarbonization: A Case Study Using the Pusan Newport International Terminal

The maritime industry is a major carbon emission contributor. Therefore, the global maritime industry puts every effort into reducing carbon emissions in the shipping chain, which includes vessel fleets, ports, terminals, and hinterland transportation. A representative example is the carbon emission reduction standard mandated by the International Maritime Organization for international sailing ships to reduce carbon emissions this year. Among the decarbonization tools, the most immediate solution for reducing carbon emissions is to reduce vessel waiting time near ports and increase operational efficiency. The operation efficiency improvement in maritime stakeholders’ port operations can be achieved using data. This data collection and operational efficiency improvement can be realized using a digital twin. This study develops a digital twin that measures and reduces carbon emissions using the collaborative operation of maritime stakeholders. In this study, the authors propose a data structure and backbone scheduling algorithm for a port digital twin. The interactive scheduling between a port and its vessels is investigated using the digital twin. The digital twin’s interactive scheduling for the proposed model improved predictions of vessel arrival time and voyage carbon emissions. The result of the proposed digital twin model is compared to an actual operation case from the Busan New Port in September 2022, which shows that the proposed model saves over 75 % of the carbon emissions compared with the case.

The Estimation of the Correlation between GHG and the Technical Efficiency of Korean Short-Sea Ports

Short-sea ports in Korea are classified as national or local according to their management and operation entities. Korea has 29 ports, of which 11 are nationally managed and 18 are locally managed. Meanwhile, according to Korea’s Harbor Act, short-sea ports are designed to support the promotion of benefits such as handling cargo required for local industries, transportation of passengers, and revitalization of tourism. However, even though they are designated as short-sea ports, there are cases in which the initial designation purpose was not achieved because of the minor traffic volume and number of passengers. Consequently, this study evaluated the operational efficiency of 29 Korean short-sea ports employing the data envelopment analysis (DEA) and presented the operational efficiency of 29 short-sea ports. Moreover, the study measured the correlation between greenhouse gas (GHG) emissions and the port operation efficiency of 29 Korean short-sea ports. The analysis results of this study are as follows: First, the correlation between port-operation efficiency and sulfur dioxide was −0.41707. Second, the correlation between efficiency and carbon monoxide was −0.39952. Third, the correlation between efficiency and nitrogen dioxide was −0.30888. In summary, this study concludes that the higher the port-operational efficiency, the lower the GHG emissions. Improving the operational efficiency of ports can reduce GHG emissions, which can positively (+) affect port sustainability.