Port Operations Research Articles

AN OVERVIEW OF THE SIMULATION CAPABILITIES FOR OPTIMIZING THE OPERATION OF THE SEAPORT IN THE ANYLOGIC ENVIRONMENT

Globalization and containerization have significantly increased the volume of shipping in international trade. A seaport is a critical component in maritime transportation. Currently, the main focus for the effective functioning of commercial ports is focused on the use of the latest information technologies. Information support of the port operation is a difficult task for a variety of reasons, the main of which is the external influence on the internal operations of the port and its overall efficiency. Simulation modeling is the most suitable tool for analyzing such a complex interaction. The article defines the characteristic features describing the specifics of the seaport operation in the AnyLogic simulation program. Various possibilities of using the established simulation model are shown to determine the limitations in the size of the throughput and processing capacity of the seaport, substantiate the need to create a “dry” port and select its main parameters.

Dynamic berth allocation under uncertainties based on deep reinforcement learning towards resilient ports

With the evolving global trade landscape and the post-pandemic effects, the resilience of ports has become paramount. The unforeseen disturbances bring substantial challenges, especially in berth allocation, a vital task ensuring seamless resilient port operations. The unpredictability of vessel arrivals and the variability in loading/unloading times intensify these issues, pushing traditional static allocation methods beyond their limits. Fortunately, the advent of smart ports has led in an era of big data availability, enabling the application of advanced deep reinforcement learning (DRL) techniques. To capitalize on this shift, this research presents a DRL-based methodology specially designed to solve the berth allocation problem with the uncertainties in vessel arrival and container handling time to enhance port resilience. A Markov Decision Process model (MDP) of the berth allocation problem is established to minimize the mean waiting time with tailored state space, rule-based action space, and reward function to address the issue. An offline training method is designed to train the agent in selecting the optimal action based on the current state of the port berth system at each decision point even in uncertain environments, deep Q-network (DQN) is implemented for this problem. Comprehensive experiments across different problem scales are conducted to validate the effectiveness and generality of the proposed method in solving berth allocation challenges under uncertain conditions. Furthermore, the trained model also performs better than other methods in different vessel congestion levels through learning.

Research and innovation identified to decarbonise the maritime sector

The maritime sector requires technically, environmentally, socially, and economically informed pathways to decarbonise and eliminate all emissions harmful to the environment and health. This is extremely challenging and complex, and a wide range of technologies and solutions are currently being explored. However, it is important to assess the state-of-the-art and identify further research and innovation required to accelerate decarbonisation. The UK National Clean Maritime Research Hub have identified key priority areas to drive this process, with particular focus on marine fuels, power and propulsion, vessel efficiency, port operations and infrastructure, digitalisation, finance, regulation, and policy.

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.

Estimating the impact of container port throughput on employment: an analysis for African countries with seaports

Ports play a significant role in facilitating international trade and economic development, serving as vital gateways for the movement of goods across the continent and beyond. As global trade volumes continue to rise, efficient port operations hold the potential to not only enhance economic growth but also contribute significantly to job creation across various sectors of the economy. This paper examines the impact of container port throughput on employment in Africa and further tests whether causality runs from employment to container port throughput. To do so, we use a sample of 27 African countries with seaport and data spanning the period from 2010 to 2020 for the analysis. The system- Generalized Method of Moments (SGMM) estimation technique is used as the estimation strategy. We use service, industrial, and total employment percentages of the total population as proxies for employment while annual container throughput measured in Twenty foots Equivalent Units (TEUs) is used as an indicator for port throughput. Based on the empirical results, we establish a positive significant effect of port throughput on employment in Africa. We further show that bidirectional causality exists between port throughput and employment in Africa. Following these findings, we recommend policies that increase port throughput in Africa.

An empirical study of the performance of the sixth generation ports model with smart ports with reference to major container ports in mainland China

Since the UNCTAD proposed the initial port model, called the first generation port model (1GP) in 1994, its adaptation and transformation have evolved, reflecting not only the evolution of port operations and technological advancements, but also the resilience of ports to natural disasters and supply disruptions. Recently, the trio of COVID-19, digitalization, and decarbonization (CDD) has emerged as core challenges whilst providing numerous opportunities for building adaption and resilience for the port industry. In light of this, the sixth generation ports (6GP) model has emerged. This paper addresses crucial research gaps by empirically testing the 6GP model, emphasizing the impact of emerging factors of the CDD, including 1) the lack of empirical testing for the 6GP model and the emphasis on the CDD; 2) the exploration of factors contributing to the significant development of Chinese container ports; 3) the investigation into how the CDD lead to the reversal of the port devolution continuum path. In doing so, an empirical study has been conducted, focusing on six major container ports in mainland China, all of which are among the world’s top 10 container ports in terms of container throughput. It evaluates the importance of the criteria of the 6GP model with the performance of the six ports. The findings of this research are discussed for managerial and policy implications, enriching the existing literature on port devolution, and providing the port industry with a holistic view of port development and strategy in the post-pandemic period.

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.

Autonomous port management based AGV path planning and optimization via an ensemble reinforcement learning framework

The rapid development of shipping trade pushes automated container terminals toward the direction of intelligence, safety and efficiency. In particular, the formulation of AGV scheduling tasks and the safety and stability of transportation path is an important part of port operation and management, and it is one of the basic tasks to build an intelligent port. Existing research mainly focuses on collaborative operation between port equipment and path optimization under environmental perception, while there is relatively little research on optimization of path smoothness and safety. Therefore, we propose a path optimization model based on the artificial potential field and twin delayed deep deterministic policy gradient (APF-TD3) framework for the port environment. Firstly, we obtain the scheduling task plan of a single AGV by enumeration. Secondly, according to the artificial potential field (APF) algorithm to generate repulsion for obstacles in the harbor and attraction for container storage at the target point with the position information of the AGV as the input data of the reinforcement learning algorithm is inputted into the twin delayed deep deterministic policy gradient algorithm (TD3). Then TD3 selects the optimal action strategy for the AGV according to the input AGV state information and the designed reward mechanism as well as executes the action. Through repeated execution, the optimal action for the next step is selected at each point to generate a path with start and end points. We validate the model by simulating the scale of containerized cargo in the port i.e. small scale, medium scale and large scale scenes. The experimental results show that the method has the shortest path length of 27.519 m, 270.847 m, and 496.389 m compared to artificial potential field and deep deterministic policy gradient (APF-DDPG), APF, and rapidly-exploring random tree (RRT) algorithms, which also have significant advantages in terms of path security and path smoothness. This framework could respond to the scheduling and transportation tasks of single AGV in different environmental layouts and guarantee the smoothness and safety of the path based on the optimization of the path, which promotes the efficient operation and management of ports.

A column generation approach for the quay crane allocation problem considering uncertain operation efficiency

This study constructs a mixed integer programming model for the integrated quay crane allocation problem to minimize vessels’ waiting time and delay time cost. Taking the uncertainty of quay crane operation efficiency into consideration, this study constructs a stochastic programming model and a distributional robust chance constraint (DRCC) model. In addition, column generation is applied to solve the three proposed models. Moreover, this paper uses real-world data from Shanghai Yangshan Port to verify the effectiveness of proposed model and algorithm. To prove the robustness of the DRCC model, this study conducts an uncertain parameters sensitivity analysis, and analyzes the performance of the models proposed above. The results show that the proposed DRCC model has better anti-interference ability. The conclusion drawn from this study has potential implications for resource allocation within port operations.

An Optimization Approach to Berth Allocation Problems

The berth allocation problem determining the berthing time and position for incoming vessels in port operations has garnered increased attention within the global transportation network. This study focuses on the berth allocation problem with a continuous quay and dynamic vessel arrivals. With the overarching goal of enhancing service quality and optimizing berth utilization rates, this article proposes a mathematical programming model that minimizes the total waiting time of vessels and the overall completion time of vessel service. The formulated model is a mixed-integer linear programming problem that deterministic optimization techniques can globally solve. For large-scale problems, this study develops a genetic algorithm optimization approach to improve computational efficiency in reaching a near-optimal solution. Several numerical experiments are conducted to demonstrate the effectiveness and efficiency of the proposed approach.

THE IMPORTANCE OF MAINTENANCE PLANNING AND CONTROL (PCM) IN THE PERFORMANCE OF MOBILE EQUIPMENT IN PORT OPERATIONS

Maintenance Planning and Control (PCM) represents one of the most important maintenance departments, as it is responsible for controlling and monitoring the company’s maintenance activities. Collecting and managing data related to maintenance, as well as costs, time, equipment availability index, average time between failures, are part of the scope of PCM management. Ports are responsible for the disposal of products, raw materials, consumer goods, among others. The logistics of these products to the ships is planned and executed with the help of equipment and machinery for handling. It is important that the available equipment available for operations with different types of cargo, be it grains, tanks, containers, others. Thus, the study aims to analyze the maintenance of transport equipment, seeking to present types of maintenance as control tools and indicators. For this reason, a theoretical approach was carried out on the logistics of cargo handling in ports, industrial maintenance, costs and financial and economic viability of the maintenance of which guide the research. The growth scenario needs increased efficiency, availability, ease of transportation combined with reduced expenses, various techniques used in the management of the maintenance sectors, this work proposes a research of the benefits of Maintenance Planning and Control (PCM) for performance of cargo handling equipment in port operations.

Cost-benefits analysis of noise abatement measures in the port of Halifax, Nova Scotia, Canada

Impacts of anthropogenic noise on human beings range from physiological to phycological and include direct damage to auditory organs, to elevated stress and annoyance, to impairments in mental development. Maritime transportation operations are also recognized as a major contributor of anthropogenic noise to nearby communities. The Port of Halifax, Nova Scotia, Canada may be a contributor to these concerns because of its noise emitting operations and it being near densely populated areas. This study examines the cost and benefits of implementing noise abatement measures to reduce potential impacts on residents by limiting road and rail traffic and cargo handling noise from Port operations. The upfront investment costs of noise abatement measures are estimated and compared to the associated human health and wellbeing benefits of reducing noise exposures in exposed residential areas. The hedonic price method was used to translate the benefits of reducing noise exposures in monetary terms. Geospatial analysis was conducted to analyze extent of dwellings exposed to unsafe levels of noise before and after the implementation of abatement measures. Total costs were calculated at $6,914,318 CAD and total benefits at $4,127,870 CAD. This equates to a return of investment of $-2,786,448 CAD. Although this may appear to be an unfavourable investment for the Port of Halifax, this study presents opportunities for improvements and recommendations for noise abatement in port operations.

The Need of Best Practices in Seaport Maintenance Management

The factors determining the world's best container port is based on the volume of container handling each year. In order to ensure that a port is able to manage high volume of containers, it is necessary for the port to provide efficient facilities from all area especially the faster turnaround time of loading and unloading operations of containers. A port is a place or area that allows ships to anchor or stop after a long voyage either on a river or in the ocean. Usually the port has at least a quay facility for ships to dock. These available facilities are to encourage import and export activities of goods or cargo to receive and send to different states or places. As an Area that functions to carry and send cargo, this necessarily requires the availability of facilities such as equipment and infrastructure to enable import and export activities to be carried out. These available facilities will be managed by a port operator appointed by a government and responsible for ensuring that all import and export activities take place in good conditions including maintenance management. The import and export process of cargo requires every port operator to know in relation to the operation's journey. This situation includes maintenance management and knowing the lifespan of each port infrastructure and equipment used for the purpose of import and export activities. The import and export activities of these goods can be in bulk and placed in containers. This shows that each port has a terminal difference which is Bulk Terminal and Container Terminal. Inside these terminals have different infrastructure and equipment to handle import and export activities.

Logical ontological modeling of cargo port risk management

Enterprises in any field, including those in the transport and logistics sector, are faced with the need to gain a competitive advantage through the use of innovative management methods. These include the integrated use of methods for managing organizational systems along with the use of advanced tools and technologies. Particular attention is paid to risk management in order to prevent undesirable situations. This paper is the first to present a description of a logical ontological model for the integrated application of multi-level goal setting based on a balanced scorecard (BSC) and logical probabilistic (LP) modeling to support decision-making on cargo port risk management. Situations of failure to achieve the goals of the cargo port, including failure to achieve standard values of indicators, are considered as risks. The integrated use of BSC and LP modeling technologies made it possible to build a general concept of multi-level goal setting. Its main advantage lies in the detailed elaboration of the company’s goals, which are subordinated to the main strategic goal. This makes it possible to influence operational events and obtain positive results in tactical and strategic plans. The ontological model contains all the information about the components interaction that influence the risk events and makes it possible to select options for exiting a risk situation in accordance with specified conditions. The results of queries to a risk-oriented ontological model are options for management decisions aimed at reducing risks in the operation of a cargo port.

Integrated planning model for two-story container ports

This study introduces a novel two-stage stochastic programming model tailored for the unique infrastructure of two-story container ports, a design that significantly enhances land productivity and operational efficiency. Our model, addressing uncertainties in vessel arrival times and container loads, incorporates advanced features like innovative quay cranes, rooftop solar panels, and dense container storage. An efficient metaheuristic is designed for large-scale applications, demonstrating a 25.63% reduction in operational costs compared to traditional decision rules. We also distill key managerial insights, notably the advantage of adopting solar power technology with consistent energy output throughout the day, offering practical guidance for port operators contemplating vertical expansion strategies.

An improved gray wolf optimization to solve the multi-objective tugboat scheduling problem.

With the continuous prosperity of maritime transportation on a global scale and the resulting escalation in port trade volume, tugboats assume a pivotal role as essential auxiliary tools influencing the ingress and egress of vessels into and out of ports. As a result, the optimization of port tug scheduling becomes of paramount importance, as it contributes to the heightened efficiency of ship movements, cost savings in port operations, and the promotion of sustainable development within the realm of maritime transportation. However, a majority of current tugboat scheduling models tend to focus solely on the maximum operational time. Alternatively, the formulated objective functions often deviate from real-world scenarios. Furthermore, prevailing scheduling methods exhibit shortcomings, including inadequate solution accuracy and incompatibility with integer programming. Consequently, this paper introduces a novel multi-objective tugboat scheduling model to align more effectively with practical considerations. We propose a novel optimization algorithm, the Improved Grey Wolf Optimization (IGWO), for solving the tugboat scheduling model. The algorithm enhances convergence performance by optimizing convergence parameters and individual updates, making it particularly suited for solving integer programming problems. The experimental session designs several scale instances according to the reality of the port, carries out simulation experiments comparing several groups of intelligent algorithms, verifies the effectiveness of IGWO, and verifies it in the comprehensive port area of Huanghua Port to get the optimal scheduling scheme of this port area, and finally gives management suggestions to reduce the cost of tugboat operation through sensitivity analysis.

Evaluation of the Availability and Feasibility of Main Land Side Facilities at the Bolok Ferry Port in Kupang City, East Nusa Tenggara Province

Construction and improvement of basic land-side facilities at the Bolok Ferry Port can support the smooth flow of mobilization of goods and passengers to optimize port operations. The aim of this research is to determine the existing conditions and analyze the need for basic land side facilities at the Bolok Ferry Port and to find out the location of the planned placement of main land side facilities based on the provisions of the applicable regulations. This research is a quantitative descriptive research, namely to determine the need for several basic facilities on the land side based on KM Number 52 of 2004 concerning the Implementation of Ferry Ports. The research results obtained show that it is necessary to increase the area of ​​the passenger terminal by 396 m2, repair and re-placement of vehicle weighers, increase the length of the way for passengers entering/exiting the ship (gangway) which directly connects to the ship's deck, adding vehicle barriers in the passenger drop-off/pick-up parking area. based on type, and adding vehicle barriers in ready-to-load parking lots based on their class. Efforts that can be made by related parties are to build and increase the area of ​​basic land-side facilities needed at the Bolok Ferry Port.

Port and inland waterway design and operation in the face of climate change uncertainty

Climate change is a key business risk for ports and inland waterways and, therefore, a key consideration for the design and operation of this infrastructure. While risk and vulnerability are typically assessed using historical information, possible future climates now also need to be considered, using quantitative climate datasets whenever possible. The current challenge is the range of availability – and levels of uncertainty – for specific parameters that are important to ports and inland waterways. When quantitative information is available, a scenario-based approach can be used to identify an appropriate range of projections for assessing risks and designing structures. Notwithstanding the availability of quantitative data, however, adaptive solutions should be favoured. This is especially important where residual uncertainty is high and/or where significant or complex investments are involved. The development of adaptation pathways enables the implementation of phased responses as climate-related hazards, such as pluvial flooding or sea-level rise, evolve. The adaptation pathway approach also reduces the risk of maladaptation associated with the assumption of a deterministic future condition for the design life of the asset or operation.

An assessment of factors for the cruise port of call selection: The modified fuzzy Analytic Hierarchy Process.

Improving cruise ports of call is essential for enhancing the overall cruise experience for passengers, promoting tourism, and supporting the economic development of the regions served by these ports. Therefore, this article aims to assess selection factors (SFs) for the cruise port of call from the perspective of cruise operators (COs) and port operators (POs). In doing so, this paper first identifies SFs for the cruise port of call and establishes their hierarchical structure thanks to the extensive literature and expert brainstorming. Afterwards, The Modified Fuzzy Analytic Hierarchy Process (MFAHP) is developed to gauge the discrepancy in SFs between COs and POs. Empirical results from MFAHP pinpoint two significant SFs for POs to improve and attract their customers: customs, immigration control and quarantine (CIQ), and incentive measures. Besides, theoretical and managerial implications, and potential limitations for the next research are discussed.

Port Sustainability Index: Methodological Issues

Approaches to find impact of maritime transport on environmental performance of ports or port regions through models with different sets of assumptions suffer from limitations. The paper describes an integrated Port Sustainability Index (PSI) by combining relevant environmental aspects of port processes and operations by transforming each indicator to follow normal distribution and taking PSI as sum of such normally distributed indicator scores, avoiding skew and outliers. Thus, there is no bias for developed or under-developed ports. PSI is simple and satisfies desired properties including assessment of effectiveness of policy measures through responsiveness, statistical tests of equality of mean PSI across ports. Dimensions of PSI can be ranked by respective elasticity. The method also helps to find growth curve of PSI of a port over time. Proposed PSI may help port authorities to evaluate their performance from the sustainability angle along with performances in the relevant dimensions and may serve as a strategic tool for port environmental performance management.