Transportation Tasks Research Articles

The Situation of Freight Transport and Other Logistics Tasks in Laos

This study aims to analyse the obstacles and constraints in the shipping and logistics in Laos, a landlocked nation in Southeast Asia. Transportation and logistics play a pivotal role in Laos' national economy, acting as the lifeblood for the movement of goods and materials within the country and linking it to the international trade system. This case study highlights the significance of a robust logistics structure for Laos and its essential role in fostering economic development, agricultural growth, and connectivity. It also underscores the challenges faced by the country's logistics sector, such as limited-service frequency and road safety concerns. The study examines Laos transportation infrastructure, encompassing road, rail, and air networks, and sheds light on the obstacles and disparities that hinder value chain development in the country. These issues include disconnected stakeholder participation, the aging vehicle fleet, and financial limitations. Furthermore, the essay emphasizes the need for improved interconnectivity and inter-mobility to enhance the national, regional, and international connectivity of Laos and similar landlocked developing countries in Asia.

Tabu search based on novel neighborhood structures for solving job shop scheduling problem integrating finite transportation resources

As advancements in transportation equipment intelligence continue, the job shop scheduling problem integrating finite transportation resources (JSPIFTR) has attracted considerable attention. Within the domain of shop scheduling, the neighborhood structure serves as a cornerstone for enabling intelligent optimization algorithms to effectively navigate and discover optimal solutions. However, current algorithms for JSPIFTR rely on generalized neighborhood structures, which incorporate operators like insertion and swap. While these structures are tailored to the encoding vectors, their utilization often leads to suboptimal optimization efficacy. To address this limitation, this paper introduces novel neighborhood structures specifically designed to the distinctive properties of JSPIFTR. These innovative structures leverage the intrinsic structural information in integrated scheduling, thereby enhancing the optimization effectiveness of the algorithm. Firstly, two theorems are presented to demonstrate the feasibility of the neighborhood solution. Secondly, different neighborhood structures for critical transportation and processing tasks are subsequently designed based on the analysis of the problem properties and constraints. Thirdly, an efficient fast evaluation method is developed to expediently calculate the objective value of the neighborhood solution. Finally, the novel neighborhood structures are combined with the tabu search (TS_NNS) and compared with other state-of-the-art methods on EX and NEX benchmarks. The comparative results demonstrate the remarkable performance of the neighborhood structure, with the TS_NNS enhancing the best solutions across 23 instances.

Architectural technology and labour organisation at the late Neolithic Liangzhu City, Yangtze Delta region, China

Building the UNESCO World Cultural Heritage site of Liangzhu City and its hinterlands was an enormous undertaking that required an unprecedented level of architectural innovations, clever logistic planning, and sophisticated labour organisation. We draw on environmental, archaeological and experimental data on the preparation and construction of grass-wrapped clay blocks at the Liangzhu City and investigate the importance of technological innovations to understand architectural energetics and labour organisation behind the unprecedented urbanisation at Liangzhu and beyond in prehistoric Yangtze Delta region. We estimate that each clay block took only around 5 min to prepare by 2–4 workers. Considering digging and other tasks, a small group of 3–4 workers would have been the most efficient arrangement in the preparation of grass-wrapped clay blocks. We reproduced different types of clay blocks, classified their sizes, and identified the standard sized (45x15 × 15cm) clay blocks that match with archaeological finds. Our results also show that standard-sized clay blocks had a more optimal grass-earth ratio which increased the drainage efficiency of the built clay-blocked structures and their resistance to weathering in wet conditions. The different architectural technologies applied by the Liangzhu builders constituted the Liangzhu builders’ earth-building toolkit. To maximize the efficiency, labour was divided and organised according to different construction tasks. The clay-blocked structures and stone beddings were mostly built by smaller groups, who were responsible for the preparation, transportation and construction tasks. Mobilization and division of labour during these construction activities might not follow the classical top-down process. Instead, the need to apply different architectural technologies, each restrained by availability of resources, convenience of transportation, and/or intrinsic engineering properties, at construction sites in a predominantly aquatic environment, prompted a creative form of labour organisation. Our study therefore provides fresh insights into understanding labour organisation, social structure and power relations at the Liangzhu Civilisation.

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Logistics distribution is one of the main sources of carbon dioxide emissions at present, and there are also such distribution problems in the shipbuilding process. With the increasing attention paid to environmental problems, how to effectively reduce the energy consumption of block transportation and improve the utilization rate of resources in the factory is the key problem that China’s shipbuilding industry needs to solve at present. This article considers the time windows for block transportation tasks, as well as the self-loading constraints of different types of flat cars, and establishes an optimization model that minimizes the empty transport time and energy consumption of the flat cars as the optimization objective. Then, an Improved Genetic Whale Optimization Algorithm is designed, which combines the cross and mutation ideas of genetic algorithms and proposes a whale individual position updating mechanism under a mixed strategy. Furthermore, the performance and computational efficiency of the algorithm are verified through comparative analysis with other classical optimization algorithms on standard test examples. Finally, the shipyard’s block transportation example proves that the energy-saving ship block transportation scheduling method can effectively improve the efficiency of shipbuilding enterprise’s block transportation and reduce the energy consumption in the block transportation process. It proves the engineering practicality of the green dispatching method proposed in this paper, which can further provide a decision-making method for shipyard managers.

Minimisation of the Energy Expenditure of Electric Vehicles in Municipal Service Companies, Taking into Account the Uncertainty of Charging Point Operation

This article presents an original method for minimising the energy expenditure of electric vehicles used in municipal service undertakings, taking into account the uncertainty in the functioning of their charging points. The uncertainty of the charging points’ operation was presented as the probability of the occurrence of an emergency situation hindering a point’s operation, e.g., a breakdown or lack of energy supply. The problem is how to calculate the driving routes of electric vehicles so that they will arrive at charging points at times at which there is a minimal probability of breakdowns. The second aspect of this problem to be solved is that the designated routes are supposed to ensure the minimum energy expenditure that is needed for the vehicles to complete the tasks assigned. The developed method is based on two heuristic algorithms, i.e., the ant algorithm and genetic algorithms. These algorithms work in a hybrid combination, i.e., the ant algorithm generates the initial population for the genetic algorithm. An important element of this method is the decision-making model for defining the driving routes of electric vehicles with various restrictions, e.g., their battery capacity or the permissible risk of charging point breakdown along the routes of the vehicles. The criterion function of the model was defined as the minimisation of the energy expenditure needed by the vehicles to perform their transport tasks. The method was verified against real-life data, and its effectiveness was confirmed. The authors presented a method of calibrating the developed optimisation algorithms. Theoretical distributions of the probability of charging point failure were determined based on the Statistica 13 program, while a graphical implementation of the method was carried out using the PTV Visum 23 software.

The Impact of Single-Use Cystoscopes on Clinical Time Workflow in an Outpatient Setting

ObjectiveTo evaluate the change in overall clinical encounter time and clinical capacity after transitioning to single-use cystoscopes (Ambu A/S, Ballerup, Denmark) in an outpatient urology setting. MethodsA single-institution prospective study in an outpatient urology procedure clinic was performed. Discrete categories for each portion of nursing care responsibilities were defined, and time spent during each category was recorded. Two separate clinic days were observed and analyzed: one where the clinic exclusively used reusable cystoscopes and the other after the transition to single-use cystoscopes occurred. Additionally, clinic schedules were reviewed from all procedure clinics in the 3-month periods before and after the transition to single-use cystoscopes. Outcomes included overall clinical encounter time and the number of procedures per clinic day. ResultsThere were 12 flexible cystoscopies performed during each of the observed clinic days. Preliminary cystoscope cleaning and transportation tasks by nursing staff were eliminated when utilizing single-use cystoscopes. Average total encounter time decreased from 66 to 44 minutes, resulting in a 34% reduction in clinical encounter time. The median number of flexible cystoscopy procedures increased after the transition from 9 (IQR 7-12) to 16 (IQR 11-17), representing a 78% increase (p=0.003). ConclusionsTransition to a completely single-use cystoscopy outpatient procedure clinic improved clinical efficiency and facilitated an increased number of procedures per clinic day.

Integration of geoinformation in transport systems

The purpose of the article is to define and apply modern scientific and practical approaches of geo-information technologies in the organization of cargo transportation using the example of the city of Kharkiv. The main task of transport is to ensure the needs of the population in meeting the needs of their movement and transportation of goods. In the presented study, the issue of integration of geo-information technologies in the process of organization of cargo transportation is solved.

The Concept of an Autonomous Mobile Robot for Automating Transport Tasks in High-Bay Warehouses

The Concept of an Autonomous Mobile Robot for Automating Transport Tasks in High-Bay Warehouses

DECENTRALIZATION AS A FACTOR IN THE DEVELOPMENT OF TERRITORIAL COMMUNITIES IN UKRAINE: EXPERIENCE OF THE EU COUNTRIES

The analysis of modern Ukrainian political and legal research suggests that the theory is dominated by the understanding of the territorial organization of power according to which the territorial community is the basis for the organization of the system of community development management. According to the researchers, it is the excessive number of small administrative-territorial units of the basic level that has determined the need for reform. The lack of the necessary economic and human resources makes it impossible for basic local government units to effectively exercise their powers. The main problem of decentralization is that the creation of new territorial communities did not take into account resource provision, transportation tasks, and economic and geographical zoning in general. The author analyzes and compares the experience of EU countries in decentralization. To ensure a favorable climate for the decentralization process, special regional development institutions have been created in different countries as executive bodies that assist various departmental structures in their activities, and these can also be independent institutions for the development of regional development programs and fund management, public non-profit organizations, and other non-governmental organizations working in partnership with government institutions. Today, in the context of war, our state as a whole and each individual territorial community in particular lives by different principles, budgets are formed and used in a completely different way, many projects have been suspended, funds allocated for them have been redirected to other areas, and mass migration has taken place both within the country and abroad.
 The article reveals that, according to the researchers, an excessive number of small administrative-territorial units of the basic level determined the need for decentralization reform. It is found that the main problem of decentralization is that the creation of new territorial communities did not take into account resource provision, transportation tasks, and economic and geographical zoning in general. The author analyzes and compares the experience of EU countries on decentralization issues. It is determined that the goals and objectives of the state policy on reform and decentralization are formed and coordinated with each other, they are specified in various programs and regulations. It can be argued that, in general, Ukraine is moving in the right direction in terms of reforming local self-government and territorial organization of power and covers all socially important areas.

Carceral Time at Port Arthur and the Tasman Peninsula: An Archaeological View of the Mechanisms of Convict Time Management in a Nineteenth Century Penal Landscape

Between 1833 and 1877 the Tasman Peninsula (Van Diemens Land/Tasmania) operated as a restricted penal zone for British convicts transported to Australia. The main penal settlement was situated at Port Arthur, with a series of substations spread across an area of 660 km2 (250 mi2). At its mid-1840s peak over 3,000 male convicts, military, and free resided on the peninsula. The vast majority of the men were engaged in diverse industrial activities, ranging from manufacturing to resource extraction, as well as the associated tasks of transport and communications. Archaeological and historical evidence demonstrates that this multiscalar penological industrial landscape was coordinated by an interlinked system of audio and visual signaling. Activity within settlements and the immediate economic hinterland was synchronized by bells, while more distant or topographically difficult sites incorporated visual signaling with time balls and semaphores. A GIS analysis of soundscapes and viewsheds shows that the latter afforded coordination of labor across the hinterland, as well as rapid complex messaging between different stations and beyond, while also spreading a net of time compliance and surveillance across the penal peninsula.

Perception–Intention–Action Cycle in Human–Robot Collaborative Tasks: The Collaborative Lightweight Object Transportation Use-Case

AbstractThis study proposes to improve the reliability, robustness and human-like nature of Human–Robot Collaboration (HRC). For that, the classical Perception–Action cycle is extended to a Perception–Intention–Action (PIA) cycle, which includes an Intention stage at the same level as the Perception one, being in charge of obtaining both the implicit and the explicit intention of the human, opposing to classical approaches based on inferring everything from perception. This complete cycle is exposed theoretically including its use of the concept of Situation Awareness, which is shown as a key element for the correct understanding of the current situation and future action prediction. This enables the assignment of roles to the agents involved in a collaborative task and the building of collaborative plans. To visualize the cycle, a collaborative transportation task is used as a use-case. A force-based model is designed to combine the robot’s perception of its environment with the force exerted by the human and other factors in an illustrative way. Finally, a total of 58 volunteers participate in two rounds of experiments. In these, it is shown that the human agrees to explicitly state their intention without undue extra effort and that the human understands that this helps to minimize robot errors or misunderstandings. It is also shown that a system that correctly combines inference with explicit elicitation of the human’s intention is the best rated by the human on multiple parameters related to effective Human–Robot Interaction (HRI), such as perceived safety or trust in the robot.

Geophysical survey based on hybrid gravimetry using relative measurements and an atomic gravimeter as an absolute reference

Gravimetry is a versatile metrological approach in geophysics to accurately map subterranean mass and density anomalies. There is a broad diversification regarding the working principle of gravimeters, wherein atomic gravimeters are one of the most technologically progressive class of gravimeters which can monitor gravity at an absolute scale with a high-repetition without exhibiting drift. Despite the apparent utility for geophysical surveys, atomic gravimeters are (currently) laboratory-bound devices due to the vexatious task of transportation. Here, we demonstrated the utility of an atomic gravimeter on-site during a gravity survey, where the issue of immobility was circumvented with a relative spring gravimeter. The atomic gravimeter served as a means to map the relative data from the spring gravimeter to an absolute measurement with an effective precision of 7.7μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\upmu }$$\\end{document}Gal. Absolute measurements provide a robust and feasible method to define and control gravity data taken at different sites, or a later date, which is critical to analyze underground geological units, in particular when it is combined with other geophysical approaches.

A novel dual-arm adaptive cooperative control framework for carrying variable loads and active anti-overturning

This paper aims to tackle the issue of carrying variable loads and disturbances in an impedance-based dual-arm robot. When robots are engaged in transportation tasks, deviations in trajectory due to changing loads and the risk of objects falling under external disturbances or unstable gripping can lead to mission failure. To address these issues, a novel Dual-Arm Adaptive Cooperative Control Framework (ACCF) is proposed. The ACCF is designed to ensure adherence to trajectory constraints in the presence of load variations and to actively respond to sliding or overturning caused by disturbances. The framework is user-friendly and robust, featuring a two-loop arrangement. The inner-loop incorporates an adaptive force control law to robustly control internal forces for dual-arm gripping. The outer-loop utilizes centralized impedance control, incorporating a fast gravity estimation scheme to compensate for trajectory deviations and an active anti-overturning scheme to resist sliding or overturning of objects during disturbances. Experimental evaluations and comparisons are conducted. The results successfully demonstrate the ACCF's adaptability under variable loads and external disturbances, providing a solution for practical dual-arm applications, such as transportation, in future scenarios.

Energy-efficient path planning for a multi-load automated guided vehicle executing multiple transport tasks in a manufacturing workshop environment.

Automated guided vehicles (AGVs) are typical intelligent logistics equipment, and path planning plays a significant role in the efficient use of AGVs. To better utilize multi-load AGVs and enhance the sustainability of the logistics process, an energy-efficient path planning model is formulated for a multi-load AGV executing multiple transport tasks in a manufacturing workshop environment, with transport distance and energy consumption (EC) serving as optimization objectives. Furthermore, a two-stage approach is proposed to solve it. In the first stage, the optimal energy-efficient paths connecting any two different nodes are acquired based on the workshop transport network expressed as a topological map. Afterward, the non-dominated sorting genetic algorithm-II is adopted in the second stage to determine the optimal execution sequence of pickup and delivery operations related to the assigned transport tasks, as well as to select the optimal path from the first stage's output information to execute each operation simultaneously. Moreover, the experimental study validates the energy-saving effect of the established model and the effectiveness of the solution method, and the factors affecting the multi-load AGV EC are analyzed.

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.

Motion Analysis of the Mug Transportation Task Through Upper Limb Kinematics

The task of transporting objects is a fundamental part of daily living activities. Previous kinematic studies focusing on tasks such as pointing, reach-to-grasp, and drinking have not fully captured the motor behaviors involved in object transportation, including placing a cup on a table or storing items in specific places. Hence, this study aimed to analyze the motor behavior associated with transporting a mug using upper limb kinematic variables. Fifteen healthy adults were instructed to transport an open-handle mug across a table. The kinematic metrics evaluated included object end-error for accuracy, frontal and lateral end-range for precision, movement time, peak velocity, time to peak velocity for control strategy, object path ratio for efficiency, and interjoint coordination. The stability of motor behavior was assessed through a test-retest analysis. The mug transporting task achieved accuracy with a radius <10 mm around the target, a peak velocity of ∼0.4 m/s, a control strategy where acceleration time constituted about 30% of the movement time, and a slightly curved trajectory. The test-retest analysis confirmed stable motor behavior across all kinematic metrics (ICCs > 0.75). Thus, the mug transporting task exhibited unique and stable kinematic characteristics, distinguishing it from non-transport activities and effectively mirroring transporting activities of daily living.

Analysis and improvement of the methodology for solving the braking task of open-pit rail transport

Analysis and improvement of the methodology for solving the braking task of open-pit rail transport

The Game Theory Application in the Transport Flows Control Algorithm Development in the Intelligent Transport System

Traffic management in modern intelligent transport systems includes monitoring the actual traffic situation in real time (volumes, speeds, incidents, etc.) and management or controlling transport traffic using this information. At the same time, cars as intelligent transport systems components must be equipped with communication capabilities for exchanging information with other vehicles (V2V) and with road infrastructure (V2I). All this is connected with the presence of special equipment connected to the on-board network for local data collection, which can be exchanged between cars and with a central communication station using wireless Internet. At the same time, the issue of developing the traffic organization algorithms themselves is still open. This problem can be solved with the help of game theory, a fairly new but rapidly developing part of modern mathematics. Unlike optimization theory, which studies the possibilities of constructing an optimal solution for the entire system as a whole, game theory studies ways to optimize individual benefits in competition with other persons (events) that rationally seek to satisfy their own benefits. The problem of “smart” regulation of intersections is quite difficult to solve, it combines the efforts of scientists from different fields of knowledge. However, the rapid development of ICT technologies and their rapid application to transport tasks makes it possible to develop some approaches to optimize the current situation at the intersection.

Study On The Improvement Of Precise Transfer Process For Critically Ill Neonates

Objective To improve the nursing strategy of critically ill neonatal transport and provide guidance for neonatal transport nursing through the study of critically ill neonatal transport. Methods From January 2020 to July 2023, according to the specific requirements and management regulations of epidemic prevention and control, our hospital established a strict and standardized transport plan, carried out transport tasks for 472 newborns who met the transport indications, and organization and management in the transport process; full security protection policy ;the improvement of transport quality and psychological support of family members were studied and analyzed. Results All 472 neonates arrived at the transport hospital safely, their condition did not worsen, their vital signs were stable, and the accompanying medical personnel and drivers did not have infection symptoms. Conclusion This study concluded that in the process of critically ill neonatal transport, the corresponding quality improvement was made in all aspects, which significantly improved the safety of transport during the epidemic period, met the needs of primary hospitals, ensured the life treatment of critically ill children, and maintained the integrity of the medical system.

Optimal Transport and Model Predictive Control-based Simultaneous Task Assignment and Trajectory Planning for Unmanned System Swarm

This paper presents a simultaneous task assignment and trajectory planning method for unmanned system swarm by using optimal transport and model predictive control (OT-MPC). Unlike the conventional hierarchical assignment and planning, the proposed approach addresses both the task assignment and trajectory planning subproblems concurrently. To be specific, a unified cost function is designed to solve task assignment and trajectory planning problem. Moreover, the multi-tasks are assigned by using optimal transport, which establishes an optimal mapping between tasks and unmanned system vehicles based on transportation cost. The trajectory planning is achieved by using model predictive control, which generates high-quality navigation trajectories considering obstacle avoidance. Finally, the proposed method is applied to the unmanned surface vehicles swarm. Numerical simulations and experiments were conducted to validate the effectiveness of the proposed method.