A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

Modeling of container terminal logistics system based on multi-agent

The similarities and differences between the container terminal logistics system(CTLS)and the Harvard-architecture computer system are compared in terms of organization and architecture.The mapping relation and the modeling framework of the CTLS are presented based on multi-agent,and the successful algorithms in the computer domain are applied to the modeling framework,such as the dynamic priority and multilevel feedback scheduling algorithm.In addition,a model and simulation on a certain quay at Shanghai harbor is built up on the AnyLogic platform to support the decision-making of terminal on service cost.It validates the feasibility and creditability of the above systematic methodology.

An integrated approach for modeling and solving the scheduling problem of container handling systems

An integrated model is presented to schedule the container handling system. The objective is to improve the coop- eration between different types of equipments, and to increase the productivity of the terminal. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence constraint, setup times and blocking (HFSS-B). A tabu search algorithm is proposed to solve this problem. The quality and efficiency of the proposed algorithm is analyzed from the computational point of view.

Peripheral Challenge in Container Port System:A Case Study of Pearl River Delta

The growth of peripheral ports to dominant hubs has been well documented in North America and Europe,and has led to the elaboration of several theoretical models.However,although changes in containerization growth have been taking place in the South and East Asia in recent years,particularly in China,only a few studies have fo-cused on this region.The Pearl(Zhujiang) River Delta(PRD) has a typical port system with hub and peripheral ports,and provides an excellent case for studying the Peripheral Challenge.This paper introduces the theoretical evidence of the Hayuth model and analyzes the evolution of the container port system in the PRD with five phases:1) phase I:preconditions for change and phase II:initial container port development in the 1970s and early 1980s;2) phase III:diffusion,consolidation,and port concentration in the middle and late 1980s;3) phase IV:the load center in the 1990s;and(4) phase V:the Peripheral Challenge since the late 1990s.The results illustrate that the Shenzhen port presents mounting challenges to the Hong Kong port,descending from a transshipment hub of China to a regional load center of Southeast China.Furthermore,this paper explores five points that have led to the evolution of the port system in the PRD:1) competition in the regional port systems;2) different interested parties;3) shift of investment strategies of in-ternational terminal operators;4) integration of shipping networks and reorganization of carriers;and 5) cost-based competition.

Container Instrumentation and Enforcement System for Runtime Security of Kubernetes Platform with eBPF

Containerization is a fundamental component of modern cloud-native infrastructure,and Kubernetes is a prominent platform of container orchestration systems.However,containerization raises significant security concerns due to the nature of sharing a kernel among multiple containers,which can lead to container breakout or privilege escalation.Kubernetes cannot avoid it as well.While various tools,such as container image scanning and configuration checking,can mitigate container workload vulnerabilities,these are not foolproof and cannot guarantee perfect isolation or prevent every active threat in runtime.As such,a policy enforcement solution is required to tackle the problem,and existing solutions based on LSM(Linux Security Module)frameworks may not be adequate for some situations.To address this,we propose an enforcement system based on BPF-LSM,which leverages eBPF(extended Berkeley Packet Filter)technology to provide fine-grained control and dynamic adoption of security policies.In this paper,we compare different LSM implementations to highlight the challenges of current enforcement solutions before detailing the design of our eBPF-based Kubernetes Runtime Instrumentation and Enforcement System(KRSIE).Finally,we evaluate the effectiveness of our system using a real-world scenario,as measuring the performance of a policy enforcement system is a complex task.Our results show that KRSIE can successfully control containers’behaviors using LSM hooks at container runtime,offering improved container security for cloud-native infrastructure.

A Study on Effective System for Harbor Container Delivery &Cargo Work Automatuion

In this article, we have attempted to analyze current situation and the problem of domestic and overseas harbor container delivery & cargo work automation centered on major harbors and to suggest effective way to deal with the issue in order to improve the productivity of container cargo work per crane, the major index of productivity of high value-added shipbuilding industry. In particular, we have suggested the way to realize effective automation system that can improve the efficiency of harbor container delivery & cargo work through the development of high-tech measuring automation technology using microwave radar and applied design that have broken away from traditional automation system and traditional problems such as dependence on manual work and the problem of laser method in which workers cannot identify laser beam under sunlight and workers’ eyesight can be weakened by being exposed to laser beam.

A Model for Predictable Capacity of a Container Terminal State： A System Dynamics Approach

Low performance of operational practices and wrong perceptions on demand forecast cause improper investments on new facilities for containers terminals, without taking into account the best use of their available resources. Accordingly, it would be desirable to model dynamic behaviour among demand, capacity and productivity of container terminal services, like reception, storage and distribution, to forecast their performances faced to demand evolution with time. This paper presents a system dynamic model to evaluate impacts from demand variations on 18 container terminals associated to ABRATEC （Associa^do Brasileira dos Terminals de Cont^ineres de Uso P^blico （in English： Brazilian Association of Public Container Terminals）） and their response capability to compensate demand growth with increasing productivity. The behaviour of the developed dynamic models was demonstrated by means of simulations carried out with the Vensim Standard 5.6d system dynamics software.

Assessment of Moisture Permeability and Closure Systems of High Density Polyethylene Plastic Bottles Used as Primary Packaging Containers for Moisture Sensitive Medicines

Introduction: Moisture permeability and a loose closure system might allow a significant gain of moisture into container and this could lead to significant loss of potency of drug sensitive to moisture and as well promoting the growth of microorganisms. Typical examples of the drugs sensitive to moisture include Tenofovir Disoproxil Fumarate (TDF). Product claimed to be a “Tight container” does not make it a tight container until proved practically. A plastic container is tight if “not more than one of the 10 tested containers exceeds 100 mg per day per L in moisture permeability. Objectives: The goal of this study was to determine rate of moisture permeability of selected High Density Polyethylene plastic bottles for packaging of moisture sensitive medicines in particular Lamivudine/Tenofovir Disoproxil fumarate tablets. Methodology: The determination of rate of moisture permeability was achieved by assessing closure systems of plastics as per USP 37 method, while the difference in absorption pattern was achieved by assessing the spectrum obtained through transmittance by Fourier Transform-Infrared (FT-IR). The plastic bottles were randomly selected from supplier A, B and C. Results: The plastic bottles from supplier A and B had an average moisture permeability of 12.57 and 51.55 mg/day/L with none of the containers exceeding moisture permeability of 100 mg/day/L whereas containers from supplier C had an average of 149.95 mg/day/L with seven of the containers exceeding of 100 mg/day/L. Conclusion: Containers from supplier A and B met the USP specifications hence could be used as primary packaging for moisture sensitive medicines whereas the containers from supplier C did not meet the USP specifications for them to be regarded as “Tight Containers” and hence, unsuitable for packaging of moisture sensitive medicines.

Promoting or Inhibiting?Influence of Railway Container Transportation on Regional Economic Development

In the context of building a country with a strong transportation network,railway container transportation(RCT)is an important means of reducing costs,increasing efficiency,and adjusting transportation structures.Thus,its impact on regional economic development is important.Based on data from railway container-handling stations and spatial econometric models,this study discusses the differences in the development of RCT and their impact on regional economic development at different leves.This study has three main findings:first,there are significant regional differences in the development of the RCT.The intra-regional differences between the eastern and central regions of China(which do not include Hong Kong,Macao and Taiwan)are gradually narrowing,while the regional differences in the western region are widening.Meanwhile,the intra-regional differences in important economic zones such as Pearl River Delta Economic Zone(PRDEZ),Chengdu-Chongqing Economic Zone(CYEZ),Bohai Rim Economic Zone(BHEZ),and Yangtze River Delta Economic Zone(YRDEZ)are narrowing daily.Second,the development differences of RCT in regional level and important economic regions level show different trends.The unbalanced features of large regions are increasingly evident,whereas the differences in economic regions are decreasing.However,the problem of overlapping RCT remains prominent.Third,the transformation of RCT development mode and fierce competition among transportation modes cause RCT to have a restraining effect on the regional economy at three levels.Rational allocation of resources and other means must be used to guide the transformation from inhibition to promotion,and by formulating targeted policies that will promote the development of RCT,which will improve the transportation structure and help construct a country with a strong transportation system.

Structural Characteristics and Evolution of a Weighted Sino-US Container Shipping Network

This study selected the Sino-US route data from the top 30 global container liner companies between December 1,2019,and December 29,2019,as the data source utilizing the complex network research methodology.It constructs a Sino-US container shipping network through voyage weighting and analyzes the essential structural characteristics to explore the network’s complex structural fea-tures.The network’s evolution is examined from three perspectives,namely,time,space,and event influence,aiming to comprehens-ively explore the network’s evolution mechanism.The results revealed that:1)the weighted Sino-US container shipping network exhib-its small-world and scale-free properties.Key hub ports in the United States include NEW YORK NY,SAVANNAH GA,LOS ANGELES CA,and OAKLAND CA,whereas SHANGHAI serving as the hub port in China.The geographical distribution of these hub ports is uneven.2)Concerning the evolution of the weighted Sino-US container shipping network,from a temporal perspective,the evolution of the regional structure of the entire Sino-US region and the Inland United States is in a stage of radiative expansion and de-velopment,with a need for further enhancement in competitiveness and development speed.The evolution of the regional structure of southern China and Europe is transitioning from the stage of radiative expansion and development to an advanced equilibrium stage.The shipping development in Northern China,the Western and Eastern United States,and Asia is undergoing significant changes but faces challenges of fierce competition and imbalances.From a spatial perspective,the rationality and effectiveness of the improved weighted Barrat-Barthelemy-Vespignani(BBV)model are confirmed through theoretical derivation.The applicability of the improved evolution model is verified by simulating the evolution of the weighted Sino-US container shipping network.From an event impact per-spective,the Corona Virus Disease 2019(COVID-19)pandemic has not fundamentally affected the spatial pattern of the weighted Sino-US container shipping network but has significantly impacted the network’s connectivity.The network lacks sufficient resilience and stability in emergency situations.3)Based on the analysis of the structural characteristics and evolution of the weighted Sino-US con-tainer shipping network,recommendations for network development are proposed from three aspects:emphasizing the development of hub ports,focusing on the balanced development of the network,and optimizing the layout of Chinese ports.

Improved STNModels and Heuristic Rules for Cooperative Scheduling in Automated Container Terminals

Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.

Impact of Hinterland Manufacturing on the Development of Container Ports: Evidence from the Pearl River Delta, China

Container ports and hinterland manufacturing are two important forces of the local participation in economic globalization.This study,taking the Pearl River Delta(PRD),China with an export-oriented economy as an example,applies Huff and panel regres-sion models to evaluate the impact of hinterland manufacturing on the development of container ports during the period of 1993–2019.The results show that 1)the spatial patterns of hinterlands for hub ports help to determine the distribution range and scale of economic variables that affect port throughput;2)the hinterland’s gross manufacturing output has universally positive influence on port through-put,wherein export-oriented processing and the entire manufacturing industry have significantly positive impact on port throughput in 1993–2011 and 2001–2019,respectively;3)the two internal structural factors related to an export-oriented economy,labor-intensive sectors and foreign-funded terminals,have positively moderate the direct influence of hinterland manufacturing on port throughput.Our results highlight the importance of local context in understanding port-manufacturing relationship in developing economies.Based on our findings,policy implications are further proposed to enhance port network organization in PRD.

Application Research on Real-Time Interactive Simulation System of Container Yard Based on Unity3D

In view of the limitations of the mathematical method used in the container terminal logistics system, this paper uses Unity3D to establish a computer simulation model for the container automated yard, which dynamically displays the operation process of the container automated yard logistics system in real time. Through the plane four-parameter coordinate conversion method and by taking the Shanghai urban construction coordinate system as the medium, it completes the conversion from the satellite positioning reference ellipsoid coordinates to the three-dimensional virtual scene coordinates. The example results show that the method is reliable and practical, improves the accuracy and efficiency of positioning, and provides a reliable reference basis for the container terminal logistics system.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.

Containment control of heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded delays

This paper addresses the problem of containment control for heterogeneous multi-agent systems subject to Markovian randomly switching topologies and unbounded communication delays.The objective is to design a distributed control strategy that ensures the output of each follower converges to the convex hull formed by the outputs of a group of leaders in mean square sense.A novel distributed observer is proposed by tackling both Markovian randomly switching topologies and unbounded delays.Then,a distributed state feedback controller and a distributed output feedback controller are developed based on the distributed observer,respectively.Finally,simulation results are provided to demonstrate the effectiveness of the proposed controllers.

Security Risk Assessment in Container Terminals:Empirical Evidence from Greece

The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.

The Influence of the Implementation of Trade Facilitation Systems on the Time Required for Creating Delivery Orders: A Case Study of Tema Port

This study evaluated the impact of Ghana’s Integrated Customs Management System (ICUMS), implemented within the National Single Window initiative, on the efficiency of issuing Delivery Orders (DO) at Tema Port. Filling a gap in the existing literature, the research employed a quantitative approach to assess a specific time-related aspect of the cargo clearance process. Employing an Independent t-test on a dataset spanning 2026 Delivery Orders (924 pre-ICUMS and 1102 post-ICUMS) from July 2020 to July 2023, the study investigated ICUMS’s effectiveness in reducing DO issuance time. Results indicate a noteworthy decrease in average DO issuance time, from 11 days pre-implementation to approximately 9 days post-implementation, a reduction validated by statistical analysis through the independent t-test. In light of these findings, the study recommends ongoing refinement of the implementation, reinforcement of trade facilitation measures, and the adoption of best practices from successful global ports. Continuous stakeholder training and regular assessments of ICUMS performance are also endorsed. The study’s implications support the theoretical framework for Single Window systems and carry significant policy implications, emphasizing the need for collaborative efforts to streamline trade facilitation processes driven by Information Technology. Practically, the results serve as a management tool for stakeholders, highlighting areas for targeted interventions to reduce DO issuance times. Methodologically, this research contributes by applying robust statistical analysis to a specific component within the Time Release Study framework, offering a nuanced understanding of trade facilitation systems’ effectiveness in improving cargo clearance processes.

Application of Random Search Methods in the Determination of Learning Rate for Training Container Dwell Time Data Using Artificial Neural Networks

Purpose: This study aimed to enhance the prediction of container dwell time, a crucial factor for optimizing port operations, resource allocation, and supply chain efficiency. Determining an optimal learning rate for training Artificial Neural Networks (ANNs) has remained a challenging task due to the diverse sizes, complexity, and types of data involved. Design/Method/Approach: This research used a RandomizedSearchCV algorithm, a random search approach, to bridge this knowledge gap. The algorithm was applied to container dwell time data from the TOS system of the Port of Tema, which included 307,594 container records from 2014 to 2022. Findings: The RandomizedSearchCV method outperformed standard training methods both in terms of reducing training time and improving prediction accuracy, highlighting the significant role of the constant learning rate as a hyperparameter. Research Limitations and Implications: Although the study provides promising outcomes, the results are limited to the data extracted from the Port of Tema and may differ in other contexts. Further research is needed to generalize these findings across various port systems. Originality/Value: This research underscores the potential of RandomizedSearchCV as a valuable tool for optimizing ANN training in container dwell time prediction. It also accentuates the significance of automated learning rate selection, offering novel insights into the optimization of container dwell time prediction, with implications for improving port efficiency and supply chain operations.

Optimizing Healthcare Big Data Processing with Containerized PySpark and Parallel Computing: A Study on ETL Pipeline Efficiency

In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the MIMIC-III Clinical Database. Our investigation entails a comprehensive exploration of various methodologies aimed at enhancing the efficiency of ETL processes, with a primary emphasis on optimizing time and resource utilization. Through meticulous experimentation utilizing a representative dataset, we shed light on the advantages associated with the incorporation of PySpark and Docker containerized applications. Our research illuminates significant advancements in time efficiency, process streamlining, and resource optimization attained through the utilization of PySpark for distributed computing within Big Data Engineering workflows. Additionally, we underscore the strategic integration of Docker containers, delineating their pivotal role in augmenting scalability and reproducibility within the ETL pipeline. This paper encapsulates the pivotal insights gleaned from our experimental journey, accentuating the practical implications and benefits entailed in the adoption of PySpark and Docker. By streamlining Big Data Engineering and ETL processes in the context of clinical big data, our study contributes to the ongoing discourse on optimizing data processing efficiency in healthcare applications. The source code is available on request.

Distributed Adaptive Predefined-Time Bipartite Containment Algorithm for Nonlinear Multi-Agent Systems with Actuator Faults

Distributed adaptive predefined-time bipartite containment for a class of second-order nonlinear multi-agent systems are studied with actuator faults.The communication topology of multi-agent systems is fixed and directed.To ensure that followers can reach the convex hull spanned by leaders under the conditions of actuator faults,the sliding mode method is introduced.Control protocol for multi-agent systems demonstrates its effectiveness.Finally,simulations are provided to verify the effectiveness of the proposed algorithm.