Browse Topic: Logistics

Items (6,938)
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, TongGu, XuefeiLi, Lingxiao
.
Xie, DongxuanLi, DongyangZhang, YoukangZhao, YingjieHong, BaofengWang, Nan
Earthmoving machines are equipped with a variety of ground-engaging tools that are joined by bolted connections to improve serviceability. These tools are made from heat-treated materials to enhance their wear resistance. Attachments on earthmoving machines, including buckets, blades, rippers, augers, and grapples, are specifically designed for tasks such as digging, grading, lifting, and breaking. These attachments feature ground-engaging tools (GET), such as cutting bits or teeth, to protect the shovel and other earthmoving implements from wear. Torquing hardened plates of bolted joint components is essential to ensure uniform load distribution and prevent premature failure. Therefore, selecting the proper torque is an important parameter. This study focuses on analyzing various parameters that impact the final torque on the hardened surface, which will help to understand the torque required for specific joints. Several other parameters considered in this study include hardware
Parameswaran, Sankaran PottiBhosale, DhanajiKumar, Rajeev
Autonomous negotiation systems, powered by artificial intelligence, are transforming supply chain management by optimizing supplier interactions. This paper proposes a framework for autonomous supplier negotiation using Statistical hypothesis testing to evaluate multiple negotiation strategies under uncertain conditions. Paper models supplier price negotiations with Random simulations, incorporating supplier cost variability and negotiation dynamics. Three strategies—distributive, integrative, and hybrid—are tested across diverse scenarios, with performance measured by negotiated price outcomes. Statistical hypothesis testing is applied to compare strategy effectiveness, identifying the hybrid approach as optimal for balancing cost savings and supplier relationships. The framework offers actionable insights into implementing autonomous negotiation systems in procurement as Agents negotiating with suppliers.
Panda, Dinesh Abhimanyu
In the agricultural industry, the logistics of transporting and storing bales, used as cattle feed, pose significant challenges for large scale farms. Traditional storage of bales in barns is labor-intensive, high in capital expenditure and requires multiple trips of transport vehicle on and off the field. Improper handling during this transition can lead to substantial losses in time, resources and loss of hay. This development aims to eliminate the last-mile transportation step, by enabling year-round storage of bales directly in the field. A patented wrapping material, along with strategic orientation of wrapped bales, enhances their resistance to weather conditions. Field experiments demonstrated that this innovative material not only protects the bales from adverse environmental factors but also effectively retains their nutrient and moisture content. A critical aspect of this solution is ensuring the correct orientation of the wrap seams, as the bales are continuously rotated
Kadam, Pankaj
The de-rated capacity of forklifts plays a crucial role in determining their safety, efficiency, and overall performance, particularly when modifications are introduced to meet stringent industrial standards. The term "de-rated capacity" refers to the reduction in a forklift's rated load-carrying capacity caused by various factors, including load center shifts, lifting height, attachment usage, tire types, and counterweight adjustments. This reduction occurs as a safety measure to account for potential instabilities or mechanical limitations when operating under less-than-ideal conditions. Accurate understanding and calculation of de-rated capacity are vital to ensure safe and efficient forklift operation. This research provides a detailed examination of forklift variants, specifically evaluated under the IS 4357:2004 standards [1], to understand the intricate relationship between tire types and counterweight adjustments on the derated capacity. With advanced Multibody Simulations, as
Shende, KalyaniShingavi, ShreyasHingade, Nikhil
Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks. The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN. This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on
Patel, Shravani Prashant
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical
Kadam, Pankaj
Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field
Singh, Rana Shakti
Weight and cost are pivotal factors in new product development, significantly impacting areas such as regulatory compliance and overall efficiency. Traditionally, monitoring these parameters across various stages involves manual processes that are often time-intensive and prone to delays, thereby affecting the productivity of design teams. In current workflows, designers must manually extract weight and center of gravity (CG) data for each component from disparate sources such as CAD models or supplier documents. This data is then consolidated into reports typically using spreadsheets before being analyzed at the module level. The process requires careful organization, unit consistency, and manual calculations to assess the impact of each component on overall system performance. These steps are not only laborious but also susceptible to human error, limiting agility in design iterations. To address these challenges, there is a conceptual opportunity to develop a system that could
Patil, VivekSahoo, AbhilashBallewar, SachinChidanandappa, BasavarajChundru, Satyanarayana
In general-purpose small SI engines, it is necessary to reduce fuel consumption under operating conditions involving repeated starts and stops. In other words, the energy distribution during the transition from 0 rpm to idling speed is a crucial factor. At startup, the SI engine must be driven by a motor, and the electrical energy required should be minimized. However, the engine must accelerate during this process, and the required electrical energy is influenced by factors such as compression, friction, and moments of inertia. The purpose of this research is to experimentally clarify the conditions for minimum energy starting in SI engines. Specifically, the effect of the moment of inertia was eliminated by using a motor to maintain a constant engine speed, thereby enabling the isolation and measurement of electrical energy consumed by friction. The electrical energy required to overcome the moment of inertia can be determined by comparing it with the energy consumed when
Matsuura, YusukeTanaka, Junya
Producing 3D models of cooling water passages of outboard motors, and calculating distribution of electric potential on the water passage surfaces using BEM, we have developed the new method for simulation of electric potential distribution. The outboard motor is a propulsion system attached to the transom of the boat with steering function. As the water around the boat is drawn in for cooling of the engine, the engine parts are susceptible to severe corrosion. As a means to help prevent corrosion, a part referred to as the anode metal, which has a lower natural potential, is provided. Such a method is called the sacrifice protection because the anode metal corrodes before the engine parts due to the difference of electric potential. Since anti-corrosion currents occur preferentially to areas close to the anode metal, the anode metal is required to be located at the most effective place for corrosion protection. However, there are certain restrictions in the layout of anode metal from
Shibuya, RyotaSuzuki, Hiroki
The arrangement of multiple cells within a battery pack is crucial to have an optimized thermal performance and pressure drop. This paper presents a comparative analysis of thermal battery cooling performance of an air-cooled battery pack using inline and staggered arrangement of 18650 sized cylindrical cells with different cell spacings. The key parameters such as air pressure drop and cell (average/maximum/minimum) temperatures are compared for operations at different C-rates, air inlet temperature, and air inlet velocities. The results demonstrate that the staggered configuration with optimal spacing offers better thermal performance and temperature distribution compared to the inline one. Specifically, the staggered setup with optimal gap achieves a lower cell average and maximum temperatures indicating more efficient cooling and uniform thermal distribution. This study highlights the advantages of battery spacing and configuration for improved thermal and pressure drop performance
Bharsakale, YashNadge, PankajManna, Suvankar
Mobile air conditioning (MAC) systems play a critical role in ensuring occupant thermal comfort, particularly under extreme ambient conditions. Any delay in compressor engagement directly affects cabin cooldown performance, impacting both perceived and measured comfort levels. This study assesses the thermal comfort risks associated with compressor engagement delays of 6.5 seconds and 13 seconds under varying ambient conditions. A comprehensive frontloading approach was employed, integrating 1D CAE simulations with objective and subjective experimental testing. Initial simulations provided insights into transient cabin heat load behavior and air distribution effectiveness, enabling efficient test case selection. Physical testing was conducted in a controlled climatic chamber under severe (>40°C) ambient condition, replicating real-world scenarios. Objective metrics, including cabin air temperature, vent temperature and cooldown rates, were measured to quantify thermal performance
Kulkarni, ShridharDeshmukh, GaneshJoshi, GauravShah, GeetJaybhay, Sambhaji
The proton exchange membrane (PEM) water electrolyzer is an emerging technology to produce green hydrogen due to its compactness and producing high purity hydrogen. This study presents a numerical investigation on multiphase flow dynamics and heat transfer within the anode flow field of a PEM water electrolyzer. Two different channel configurations, i.e., rectangular, semi-circular are considered having same cross-sectional area while keeping the porous transport layer (PTL) thickness constant (which is within the commercially available ranges). Simulations are conducted for various oxygen generation rates and heat fluxes (corresponding to different current densities) and different inlet water flow rates. The effects of channel configurations on pressure drop, flow uniformity, and temperature distribution are illustrated pictorially and graphically. The impact of water flow rates and oxygen generation rates on phase distribution, pressure drop, and temperature profiles, particularly
Dash, Manoj KumarBansode PhD, Annasaheb
Discovering the trend of risk changes and formulating risk prevention and control measures are important links in achieving proactive risk prevention and control. Constructing and analyzing field models can visualize the distribution and change of risks and formulate effective risk prevention and control measures. Based on the current situation and trend of field model research, this paper discusses its application in risk identification, aiming to improve the accuracy of risk avoidance. Firstly, different types of field models are classified, and their respective characteristics and application scenarios are introduced. Secondly, the shortcomings in the development of field models are summarised. Finally, in the field of autonomous driving and intelligent traffic management, it is proposed that the accuracy of the model can be improved by multi-scene data fusion, the dynamic response enhances the efficiency of risk avoidance, and the aspect of risk classification in complex
Song, YulianYue, LihongWang, Chunxiao
River regulation engineering is pivotal for harmonizing flood resilience, ecological integrity, and navigation efficiency in large alluvial systems, particularly under intensified hydrological stressors. The Yangtze River, Asia’s largest fluvial network, has experienced altered hydro-sedimentary regimes and exacerbated channel instability due to cascade reservoir operations, demanding adaptive strategies to stabilize dynamic reaches. This study investigates hydrodynamic and flow distribution responses to integrated regulation measures in the Chizhou Reach—a vulnerable alluvial segment characterized by severe bank erosion, sedimentation-induced flow imbalances, and constrained floodplains. Using a 1:500/1:100 scaled hydraulic model validated under flood and low-flow conditions, we assess synergistic effects of dredging, submerged dams, and flow-regulating groynes. Here we show that dredging the Wanchuanzhou right branch increases its flow diversion ratio by 1.71% (annual average flow
Gao, JinFeng, LileiRuan, JunshengLu, LixinYan, Jun
With the rapid development of autonomous driving technologies, intelligent ports, particularly autonomous logistics, have become the focus of industry attention. Ensuring safe and efficient operations require port management systems to perceive and predict the behaviors of people and vehicles. In the filed of behavior perception, research efforts have primarily focused on the detection and tracking of vehicles, pedestrians, and obstacles under various sensor configurations. Common approaches include vision-based, LiDAR-based, and multi-sensor fusion methods. In terms of behavior prediction, existing approaches can be broadly categorized into four paradigms: model-driven, data-driven, environment-assisted, and anomaly prediction methods. Model-driven approaches rely on physical and motion models, while data-driven approaches utilize deep learning techniques. Environment-assisted approaches integrate prior knowledge such as maps, while anomaly prediction focus on identifying unexpected
Lu, ZhiyongWang, XiyuanLiu, ShiquYang, ZhengLi, HaoHe, Xiaofei
Cargo Routing Problem or Container Allocation Problem is key decision-making challenge in the maritime industry at operational level. Existing research focus on static environment or planning decisions, ignoring the dynamic arrival property of shipping request in practical world. In this paper, we introduced the Online Cargo Routing problem and formulation the path-based models under a space-time network. We proposed an online algorithm under the online primal-dual scheme: re-solving strategy. We further conducted simulation experiments under different demand distributions to demonstrate the performance of the proposed algorithm over the offline baselines.
Xu, XiaoweiGong, LinXiang, XiLiu, Xin
With the development of e-commerce and urbanization, logistics distribution has become a key challenge in improving traffic management and efficiency. The use of parcel lockers can alleviate delivery pressure, enhance user experience, and reduce costs. This paper investigates the Multi-Objective Vehicle Routing Problem with Parcel Lockers (MOVRPPL), aiming to optimize transportation costs, customer satisfaction, and the number of vehicles to improve resource utilization. Based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II), this paper proposes the NSGA-II-NI algorithm, which incorporates the nearest neighbor crossover algorithm and route optimization to approximate the Pareto optimal solution set. Experiments using the Solomon dataset are conducted, and the performance is evaluated using the Inverted Generational Distance (IGD) and Hypervolume (HV), compared with the state-of-the-art algorithm NSGA-II-HI. The experimental results show that our method achieves a better
Liu, YuxinWang, Ying
This study focuses on analyzing the impact of the Francis Scott Key Bridge collapse on traffic flow and the traffic network in Baltimore City. By employing the processing of publicly available datasets, the construction of a traffic network model and a comprehensive scoring method and an improved K-means clustering algorithm based on the idea of the rotational method, the following conclusions have been drawn in this study. First, the bridge collapse significantly changed the distribution of traffic flow. According to the AADT data of 17 key traffic nodes, after the bridge collapse, the AADT of all nodes generally increased except for the nodes closest to the tunnel and bridge. For example, traffic nodes around the city center (e.g., nodes with OSMID numbers 37831627 and 602433660) experienced an increase in AADT, suggesting that traffic flows we Second, the 17 key nodes selected represent the major nodes of the Baltimore City traffic system and provide accurate data to support
Hao, ZhenxiangHu, JianpingRan, JinZheng, YuhangMa, Chenyuan
In the past half - century, China’s reclamation area has exceeded 15,000 km2, making it the country with the largest reclamation area in the world. Among them, 3% of the area of the Bohai Sea has been reclaimed, and the land - sea changes are very significant, making accurate and continuous monitoring and analysis of the area necessary. Starting from “dynamic monitoring - utilization analysis”, this paper studies the dynamic spatial distribution and quantitative changes of reclaimed areas in Bohai Bay based on the yearly remote sensing images from 1974 to 2023, using ENVI and GIS technologies. In the past 40 years, a total of 1379.79 km2 of the sea area has been reclaimed in the study area, mainly in the inshore and tidal flats. The land - use change map shows that land - use changes are closely related to policy and economic mode changes. Under the five - year time slice, the comprehensive land - use degree of the Bohai Bay is less than 4%, showing an extremely slow chagne.
Li, YiZhu, Gaoru
In recent years, the vibration comfort of automobiles has become a key consideration for consumers when purchasing vehicles. This study introduces human electrocardiogram (ECG) signals and blood pressure, and proposes a comfort prediction model based on physiological indicators. The research steps include: obtaining riding indicators and subjective feelings on flat and bumpy roads, and analyzing the differences in heart rate variability indicators and blood pressure under different road conditions through paired sample tests; playing different sound signals on bumpy roads, and using repeated measures analysis of variance to explore their impacts on physiological indicators and subjective evaluations; conducting data validity tests on the subjective evaluation results, and constructing a comfort prediction model based on correlation analysis and support vector regression algorithm. The results show that there are significant differences in indicators such as the average RR interval and
Hu, LiChen, HaoWan, YeqingTian, RuiliXu, Jiahao
With the rapid increase in the number of electric vehicles, the rational placement of battery swapping stations has become a critical issue in optimizing urban transportation infrastructure. This paper proposes a site selection optimization method based on Graph Neural Networks (GNN). By constructing an urban transportation graph model grounded in Points of Interest (POI) and road traffic data, the method analyzes battery swapping station layout plans and validates their robustness and scalability. Taking the main urban area of Nanchang City as a case study, the research integrates data on POI distribution and land-use functional diversity within buffer zones to construct a graph structure. It then employs GNN for node classification to identify optimal battery swapping station locations. Experimental results show that, compared to traditional methods, the proposed approach improves site selection accuracy by 15% and enhances optimization efficiency by 20%. This method can provide
Zeng, YiYi, Xinyu
In order to determine the actual position of the beacon buoy, improve the casting accuracy of the beacon buoy, and reduce the frequency of the beacon buoy being hit, the mean shift model of the sinker location was established according to the real-time position data of the beacon telemetry and remote control, and the probability density distribution of the beacon buoy position was obtained and the actual position of the beacon buoy was analyzed. In order to ensure the comprehensiveness and accuracy of the research results, real-time data of light buoy positions in different sea areas and at different times were selected, and MATLAB simulation experiments were conducted to compare the actual sinker location with the designed position. The experimental results show that the mean shift algorithm can accurately predict the actual position of the stone, which provides a useful reference for improving the casting accuracy of the Marine light buoy.
Liu, HuanSong, ShaozhenJu, XinLin, Xiaozhuo
This study extends the bottleneck model to analyze dynamic user equilibrium (UE) in carpooling during the morning peak commute. It is assumed that the carpooling platform offers both traditional human-driven vehicles and novel shared autonomous vehicles. First, we analyze the traffic distribution on a two-lane road. We find that traffic distribution is influenced by the additional cost of carpooling behavior. A corresponding functional relationship is established and visualized. Second, we derive the critical fare threshold for carpooling. Carpooling occurs only when the fare is below this threshold. Third, we obtain the user equilibrium (UE) solution under a specified case, including flow distribution, equilibrium cost, and total number of vehicle. Furthermore, a system-optimal dynamic tolling scheme is proposed to minimize total system cost while maintaining commuter UE. By equating the system marginal cost to the equilibrium cost, we derive the analytical expression for the lane
Zheng, XiaoLongZhong, RenXin
On highways, platoons of semi-trucks are a common phenomenon. By maintaining a small headway, these platoons can effectively reduce air resistance, thereby improving fuel efficiency and reducing carbon emissions. However, this driving mode is also accompanied by many safety and operational risks, such as increased risk of rear-end collisions, reduced driving comfort, and susceptibility to interference from other vehicles outside the platoon. Therefore, behavioral analysis and evaluation of semi-truck platoons naturally formed in real traffic environments are of great significance for improving their driving safety, comfort and stability. This study focuses on the headway characteristics of semi-truck platoons, analyzes their headway distribution, headway gap and braking response behavior, and then proposes a safe headway threshold for emergency braking to effectively reduce the probability of rear-end collisions. In addition, the study also defines an optimal headway range to reduce
Hu, XiaoqiangCao, Qiang
Aiming at the dynamic customer demand for multiple products in different cycles, with the lowest total cost of the distribution system as the goal, taking into account distribution centre capacity, vehicle loading and other resource constraints, vehicle loading and other resource constraints, we constructed a two-layer objective planning model of distribution centre siting-vehicle path optimization. The upper model is solved by Gurobi to obtain the distribution centre location and customer division scheme, the greedy algorithm will be applied to solve the initial vehicle path planning, and then uses the particle swarm algorithm for optimisation to obtain the corresponding location scheme and vehicle scheduling scheme. Taking an automotive aftermarket spare parts data as an example, the distribution centre site selection and vehicle path scheme are determined in t1and t2 cycles respectively, and the findings indicate that the model can be effective in reducing the possible waste of the
Zhu, JunrongZhang, Liping
The study investigated the fluid dynamics characteristics of a navigational body during emerging from water. It focus on the patterns of pressure and velocity changes in the flow field. Using numerical simulation methods, we explored the fluid-structure interaction between the navigational body and the surrounding water. It revealed the phenomenon of decreasing impact forces on the object’s surface over time and the resulting changes in surface pressure distribution. Additionally, the study demonstrated the dynamic evolution of the velocity field during emergence. This further elucidated the impact of flow state changes on the navigational body’s motion performance and stability. These findings would provide important theoretical foundations and technical support for optimizing the design of navigational bodies.
Zhang, ChaoyangZhang, ZhihuaLiu, ZongkuiSui, Jiuling
Use Decision Making Trial and Evaluation Laborator (DEMATEL) and Analytic Hierarchy Process (AHP) to jointly analysis and determine the key factors of Guangzhou intelligent logistics. Through the questionnaire survey of 92 logistics enterprises in Guangzhou, it is concluded that Information infrastructure, big data, Internet of Things, artificial intelligence, Logistics dynamic updates, and Smart warehousing have a great impact on intelligent logistics. Combining practical engineering with theory to make the implementation of Guangzhou’s smart logistics project more scientific, It is characterized by a higher degree of scientificity. Moreover, it is of great warning value, which can alert relevant parties to potential issues. Meanwhile, it provides essential guidance for the implementation of the smart city project in Guangzhou, facilitating a more efficient and well - directed execution process. This study is limited to logistics business respondents in Guangzhou and may limit the
Zhang, ShuangshuangChen, NingKhaw, Khai WahLiu, ChenxiJin, Lili
Items per page:
1 – 50 of 6938