Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under ext...Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under external stimulation.However,most microrobots are currently made of a single material system and focus on fabricating a driving module as the main structure of microrobots.This hinders the integration of diverse functions in one microrobot to fulfill the complex application.Here,a multi-material and multi-module hand-microrobot based on femtosecond laser direct writing technology is proposed,which has a pH-responsive capturing module and a magnetic-responsive transportation module(MRTM).This microrobot can not only respond to pH for capturing and releasing objects,but also respond to magnetic fields for cargo delivery even with obstacles.The two responding modules of the hand-microrobot are fabricated independently,and can collaborate with each other to achieve the delivery of target objects like polystyrene(PS)microsphere(10µm)or 786-O cell by capturing,transporting,and spatial rolling.Besides,the MRTM can be locally fabricated on any prefabricated static structure,so that the whole microrobot can achieve controllable motion.This strategy is expected to be used to manipulate cells,deliver drugs for precise treatment,and environmental treatment.展开更多
The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review exa...The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.展开更多
The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Tradit...The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Traditional intrusion detection systems have limitations in terms of centralized architecture,lack of transparency,and vulnerability to single points of failure.This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems.This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signaturebased intrusion detection system.The introduced signature facilitates accurate detection and systematic classification of attacks,enabling categorization according to their severity levels within the transportation infrastructure.Through comparative analysis,the research demonstrates that the blockchain-based IDS outperforms traditional approaches in terms of security,resilience,and data integrity.展开更多
The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and ...The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and transportation in a superfluid^(4)He(SFHe,He-Ⅱ)source accurately.This limitation arose from the absence of an^(4)He upscattering mechanism and the absorption of^(3)He.And the provided source energy distribution in MCUCN is different from that in SFHe source.This study introduced enhancements to MCUCN to address these constraints,explicitly incorporating the^(4)He upscattering effect,the absorption of^(3)He,the loss caused by impurities on converter wall,UCN source energy distribution in SFHe,and the transmission through negative optical potential.Additionally,a Python-based visualization code for intermediate states and results was developed.To validate these enhancements,we systematically compared the simulation results of the Lujan Center Mark3 UCN system by MCUCN and the improved MCUCN code(iMCUCN)with UCNtransport simulations.Additionally,we compared the results of the SUN1 system simulated by MCUCN and iMCUCN with measurement results.The study demonstrates that iMCUCN effectively simulates the storage and transportation of ultracold neutrons in He-Ⅱ.展开更多
The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability ...The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability and facilitates automatic control in the ITS environment.The exponential increase in IoT nodes has significantly increased the demand for an energy-efficient,mobility-aware,and secure system for distributed intelligence.This article presents a mobility-aware Deep Reinforcement Learning based Federated Learning(DRL-FL)approach to design an energy-efficient and threat-resilient ITS.In this approach,a Policy Proximal Optimization(PPO)-based DRL agent is first employed for adaptive client selection.Second,an autoencoder-based anomaly detectionmodule is considered for malicious node detection.Results reveal that the proposed framework achieved an 8%higher accuracy increase,and 15%lower energy consumption.Themodel also demonstrates greater resilience under adversarial conditions compared to the state of the art in federated learning.The adaptability of the proposed approach makes it a compelling choice for next-generation vehicular networks.展开更多
Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-netwo...Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.展开更多
Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transporta...Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transportation systems(ITS).This paper presents a systematic review of ILC's developmental progress,current methodologies,and practical implementations across these two critical domains.The review first analyzes the key technical challenges encountered when integrating ILC into precision manufacturing workflows.Through case studies,it evaluates demonstrated improvements in positioning accuracy,surface finish quality,and production throughput.Furthermore,the study examines ILC’s applications in ITS,with particular focus on vehicular motion control applications including autonomous vehicle trajectory tracking,platoon coordination,and traffic signal timing optimization,where its data-driven characteristics enhance adaptability to dynamic environments.Finally,the paper proposes targeted future research directions that are essential for fully realizing ILC’s potential in advancing these interconnected yet distinct fields.展开更多
As urbanization continues to accelerate,the challenges associated with managing transportation in metropolitan areas become increasingly complex.The surge in population density contributes to traffic congestion,impact...As urbanization continues to accelerate,the challenges associated with managing transportation in metropolitan areas become increasingly complex.The surge in population density contributes to traffic congestion,impacting travel experiences and posing safety risks.Smart urban transportation management emerges as a strategic solution,conceptualized here as a multidimensional big data problem.The success of this strategy hinges on the effective collection of information from diverse,extensive,and heterogeneous data sources,necessitating the implementation of full⁃stack Information and Communication Technology(ICT)solutions.The main idea of the work is to investigate the current technologies of Intelligent Transportation Systems(ITS)and enhance the safety of urban transportation systems.Machine learning models,trained on historical data,can predict traffic congestion,allowing for the implementation of preventive measures.Deep learning architectures,with their ability to handle complex data representations,further refine traffic predictions,contributing to more accurate and dynamic transportation management.The background of this research underscores the challenges posed by traffic congestion in metropolitan areas and emphasizes the need for advanced technological solutions.By integrating GPS and GIS technologies with machine learning algorithms,this work aims to pay attention to the development of intelligent transportation systems that not only address current challenges but also pave the way for future advancements in urban transportation management.展开更多
Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along ...Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along the Primorsky No.1 and No.2 transportation corridors.First,the evaluation of urban accessibility level with and without Primorsky No.1 and No.2 high-speed rails(HSRs)opening was conducted with two indicators,i.e.,the weighted average travel time,and the economic potential.After the evaluation,the spatial differentiation pattern of the accessibility changes with and without Primorsky No.1 and No.2 HSRs opening was performed respectively using ArcGIS.On these bases,the regional spatial effects brought by Primorsky No.1 and No.2 HSRs opening were studied.The results are as following.First,the urban accessibility level will be greatly improved by the opening of Primorsky No.1 and No.2 HSRs.All adjacent cities will be integrated into‘1 h HSR communication circle’and the whole journey will be integrated into‘4 h HSR communication circle’along Primorsky No.1 and No.2 corridors,respectively.The HSR accessibility of Primorsky No.1 corridor is stronger than that of Primorsky No.2 corridor.But the HSR accessibility improvement degree of Primorsky No.1 corridor is weaker than that of Primorsky No.2 corridor.Second,spatially,along Primorsky No.1 and No.2 corridors,the HSR accessibility level of the cities which are located in China is stronger than those cities located in Russia,showing the‘High West,Low East’patterns.The HSR accessibility improvement degree of the cities which are located in Russia and Sino-Russian border is stronger than those cities located in China,showing the‘High East,Low West’patterns.Third,Primorsky No.1 and No.2 corridors could connect the China’s‘Heilongjiang Land Sea Silk Road Economic Belt’and‘Changchun-Jilin-Tumen Development Pilot Zone’respectively,gradually involving into the development of China’s Harbin-Changchun Megalopolis.Relying on Harbin(China)and Changchun(China),Primorsky No.1 and No.2 HSRs could connect Northeast China-Beijing HSR,accelerating the diffusion of population,economy and other flows from China’s Beijing-Tianjin-Hebei Urban Agglomeration to Northeast China,and then to Russia’s Far East Federal District.Relying on Suifenhe(China)and Hunchun(China),Primorsky No.1 and No.2 HSRs could be conducive to the development of the second largest sea channels for Northeast China,creating the Northeast Asian Urban Belt,and new sea-rail intermodal pattern among China,Russia,Democratic People’s Republic of Korea,Japan and Republic of Korea.Relying on Vladivostok(Russia)and Zarubino(Russia),Primorsky No.1 and No.2 corridors could connect the‘Ice Silk Road’,building the‘Sino-Russian Northern Maritime Corridor’and‘Sino-Russian Arctic Blue Economic Areas’.展开更多
To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains i...To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.展开更多
Solid lipid nanoparticles(SLN)could enhance the oral bioavailability of loaded protein and peptide drugs through lymphatic transport.Natural oligopeptides regulate nearly all vital processes and serve as a nitrogen so...Solid lipid nanoparticles(SLN)could enhance the oral bioavailability of loaded protein and peptide drugs through lymphatic transport.Natural oligopeptides regulate nearly all vital processes and serve as a nitrogen source for nourishment.They are mainly transported by oligopeptide transporter-1(PepT-1)which are primarily expressed in the intestine with the characteristics of high-capacity and low energy consumption.Our preliminary research discovered the transmembrane transport of SLN could be improved by stimulating the oligopeptide absorption pathway.This implied the potential of combining the advantages of SLN with oligopeptide transporter mediated transportation.Herein,two kinds of dipeptide modified SLN were designed with insulin and glucagon like peptide-1(GLP-1)analogue exenatide as model drugs.These drugs loaded SLN showed enhanced oral bioavailability and hypoglycemic effect in both type I diabetic C57BL/6mice and type II diabetic KKAymice.Compared with un-modified SLN,dipeptide-modified SLN could be internalized by intestinal epithelial cells via PepT-1-mediated endocytosis with higher uptake.Interestingly,after internalization,more SLN could access the systemic circulation via lymphatic transport pathway,highlighting the potential to combine the oligopeptide-absorption route with SLN for oral drug delivery.展开更多
Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportatio...Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.展开更多
Smart transportation is a key direction and trend in the development of China’s public transportation sector.Under this background,new opportunities for the development of transportation engineering education have em...Smart transportation is a key direction and trend in the development of China’s public transportation sector.Under this background,new opportunities for the development of transportation engineering education have emerged,necessitating the active promotion of hybrid teaching in transportation engineering courses.This approach aims to achieve innovation in teaching content and enhance the quality and effectiveness of education.Therefore,to improve the quality of transportation engineering education,this paper conducts research and exploration on the reform of hybrid teaching content.It proposes several measures,including constructing a dynamic teaching content system,strengthening faculty education and training,improving teaching facilities and technical support,and reinforcing students’self-discipline in learning.These initiatives aim to promote the reform of transportation engineering courses under the current smart transportation background and enhance the overall level and quality of education.展开更多
The Chengdu-Chongqing twin city economic circle has become a national strategy.As the westwards gateway of Chongqing central city,the High-tech Zone should further strengthen its traffic integration and interconnectiv...The Chengdu-Chongqing twin city economic circle has become a national strategy.As the westwards gateway of Chongqing central city,the High-tech Zone should further strengthen its traffic integration and interconnectivity with the Chengdu-Chongqing main Corridor.Combining the design concept and functional positioning of Jinfeng Hub,the research should be carried out from the aspects of hub scale control,three-dimensional spatial layout,rail transit connection,road collection and distribution system construction,and integrated development with the city.It is expected to provide a good reference for the planning and design of modern integrated transportation hub.展开更多
Inactivation of carbon-based transition metal catalysts,which was caused by electron loss,limited their application in advanced oxidation processes.Therefore,Co and TiO_(2) double-loaded carbon nanofiber material(Co@C...Inactivation of carbon-based transition metal catalysts,which was caused by electron loss,limited their application in advanced oxidation processes.Therefore,Co and TiO_(2) double-loaded carbon nanofiber material(Co@CNFs-TiO_(2))was synthesized in this study.Photocatalytic and chemical catalytic systems were synergized efficiently.Tetracycline was eliminated within 15 min.The degradation rate remained above 90%after five cycles,and the 50%promotion proved the high stability of Co@CNFs-TiO_(2).The main reactive oxygen species in this system were sulfate radicals,whereas Co and TiO_(2) represented the active sites of the catalytic reaction.Electrons generated from TiO_(2) during the photocatalytic process were transferred to Co,which promoted the Co(Ⅲ)/Co(Ⅱ)cycle and maintained Co in a low-valence state,thereby stimulating the generation of sulfate radicals.In this study,the effective regulation of reactive oxygen species in the reaction system was realized.The results provided a guidance for in situ electron replenishment and regeneration of carbon-based transition metal catalysts,which will expand the practical application of advanced oxidation processes.展开更多
Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies a...Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies across production,storage,transportation,and utilization.On the production side,electrolysis and solar‐driven photocatalysis are rapidly advancing toward industrial adoption,yet remain constrained by electrolysis efficiency,cost,and electrolyzer durability.For storage and transportation,lowering costs and energy consumption,improving system efficiency,and deploying safe,high‐capacity hydrogen storage and transportation solutions are key priorities.Regarding hydrogen utilization,particularly hydrogen fuel cells and hydrogen‐based power systems,require further enhancement in their durability,reliability,and integration flexibility to enable widespread deployment across sectors.Therefore,this review provides a comprehensive overview of green hydrogen technologies,emphasizing recent advances,key challenges,and industrial demonstrations.By integrating insights from electrochemical and photochemical production,solid‐state and liquid‐phase storage,and hydrogen end‐use pathways,we propose a roadmap toward the scalable deployment of green hydrogen infrastructure.Coordinated progress across these domains will position hydrogen as a cornerstone of a sustainable,secure,and decarbonized global energy solution.展开更多
Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into th...Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into the modern logistics system.It seeks to address the need for a more nuanced understanding of the“road to rail”policy,emphasizing the importance of intermodal collaboration and service of fragmented market demands.Design/methodology/approach–The study employs a transport economics perspective to evaluate the achievements and shortcomings of China’s transportation structure optimization.It bases its assessment of the current state of railway freight logistics,multi-modal transportation and the broader implications for the transportation service market on data analysis.The methodology includes a review of existing policies,an examination of industry practices and a comparative analysis with global trends in railway logistics.Findings–The research underscores the importance of focusing on the development of non-bulk materials,noting the insufficiency in the development of China’s rail multi-modal transportation and highlighting the instructive value of successful cases in open-top container road-rail intermodal transportation.The study posits that the railway sector must enhance cooperation with other market entities,aligning with the lead enterprises in the logistics chain that are characterized by speed,high value and strong coordination capabilities,in order to better serve the transportation market.This approach moves away from a reliance on the railway’s own capabilities alone.Originality/value–This paper offers original insights into the transformation of railway freight in China,contributing to the body of knowledge on transportation economics and logistics.It provides valuable recommendations for policymakers and industry practitioners,emphasizing the strategic importance of railway logistics in the context of China’s economic development and intense competition in the supply chain.The value of the article lies in its comprehensive understanding of the complexities involved in the adjustment of transportation structures,providing direction for the market-oriented reform of China’s railway freight sector.展开更多
The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of mana...The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of managing personal moisture/thermal comfort in response to changing external environments remains a challenge.Herein,a smart cellulose-based Janus fabric was designed to dynamically manage personal moisture/heat.The cotton fabric was grafted with N-isopropylacrylamide to construct a temperature-stimulated transport channel.Subsequently,hydrophobic ethyl cellulose and hydrophilic cellulose nanofiber were sprayed on the bottom and top sides of the fabric to obtain wettability gradient.The fabric exhibits anti-gravity directional liquid transportation from hydrophobic side to hydrophilic side,and can dynamically and continuously control the transportation time in a wide range of 3–66 s as the temperature increases from 10 to 40℃.This smart fabric can quickly dissipate heat at high temperatures,while at low temperatures,it can slow down the heat dissipation rate and prevent the human from becoming too cold.In addition,the fabric has UV shielding and photodynamic antibacterial properties through depositing graphitic carbon nitride nanosheets on the hydrophilic side.This smart fabric offers an innovative approach to maximizing personal comfort in environments with significant temperature variations.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integ...With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integrated molding and design freedom,is a powerful catalyst for distributed manufacturing.This paper investigates the integrated production and transportation scheduling problem in distributed 3D printing.To solve this problem,we decompose the original problem into three sub-problems and design a multilevel optimization algorithm.We employ a genetic algorithm in the outer-level optimization to determine the optimal allocation of parts to machines.In the inner-level optimization,we utilize a simulated annealing algorithm to tackle the vehicle routing problem during the transportation stage followed by a local search algorithm to address the scheduling problem encountered during the production stage.Our algorithm is validated using real data from a 3D printing company,and the results show that our algorithm can obtain solutions that are the same as or better than those of Gurobi in a reasonable time for small-sized instances.Additionally,three types of initial methods are tested on large-sized instances to verify the efficiency of the proposed algorithm,and some interesting insights are also revealed and discussed.展开更多
基金financial support of the National Key R&D Program of China(Grant Nos.2024YFB4607402 and 2016YFA0200500)National Natural Science Foundation of China(NSFC,Grant Nos.61975213,61475164 and 61205194)International Partnership Program of Chinese Academy of Sciences(GJHZ2021130)。
文摘Microrobots play an essential role in early diagnosis and precision medicine with the increasing demands for controllability in bio-medicine and micromanipulation,which can complete the pre-designed behavior under external stimulation.However,most microrobots are currently made of a single material system and focus on fabricating a driving module as the main structure of microrobots.This hinders the integration of diverse functions in one microrobot to fulfill the complex application.Here,a multi-material and multi-module hand-microrobot based on femtosecond laser direct writing technology is proposed,which has a pH-responsive capturing module and a magnetic-responsive transportation module(MRTM).This microrobot can not only respond to pH for capturing and releasing objects,but also respond to magnetic fields for cargo delivery even with obstacles.The two responding modules of the hand-microrobot are fabricated independently,and can collaborate with each other to achieve the delivery of target objects like polystyrene(PS)microsphere(10µm)or 786-O cell by capturing,transporting,and spatial rolling.Besides,the MRTM can be locally fabricated on any prefabricated static structure,so that the whole microrobot can achieve controllable motion.This strategy is expected to be used to manipulate cells,deliver drugs for precise treatment,and environmental treatment.
文摘The concept of Cyber-Physical Systems(CPS)enables the creation of a complex network that includes sensors integrated into vehicles and infrastructure,facilitating seamless data acquisition and transfer.This review examines the convergence of CPS and Industry 4.0 in the smart transportation sector,highlighting their transformative impact on Intelligent Transportation Systems(ITS)operations.It explores the integration of Industry 4.0 and CPS technologies in intelligent transportation,highlighting their roles in enhancing efficiency,safety,and sustainability.A systematic framework is proposed for developing,implementing,and managing these technologies in the transportation industry.Moreover,the review discusses frequent obstacles during technology integration in transportation and presents future research trends and innovations in intelligent transportation operations post-Industry 4.0 and CPS integration.Lastly,it emphasizes the critical need for standardized protocols and encryption methodologies to enhance the security of communication and data exchange among CPS components in transportation infrastructure.
基金supported by the National Research Foundation(NRF),Republic of Korea,under project BK21 FOUR(4299990213939).
文摘The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats,making intrusion detection a critical aspect of ensuring their secure operation.Traditional intrusion detection systems have limitations in terms of centralized architecture,lack of transparency,and vulnerability to single points of failure.This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems.This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signaturebased intrusion detection system.The introduced signature facilitates accurate detection and systematic classification of attacks,enabling categorization according to their severity levels within the transportation infrastructure.Through comparative analysis,the research demonstrates that the blockchain-based IDS outperforms traditional approaches in terms of security,resilience,and data integrity.
基金the National Key R&D Program of China(No.2024YFE0110001)the National Natural Science Foundation of China(U1932219)the Mobility Programme endorsed by the Joint Committee of the Sino-German Center(M0728)。
文摘The ultracold neutron(UCN)transport code,MCUCN,designed initially for simulating UCN transportation from a solid deuterium(SD_2)source and neutron electric dipole moment experiments,could not simulate UCN storage and transportation in a superfluid^(4)He(SFHe,He-Ⅱ)source accurately.This limitation arose from the absence of an^(4)He upscattering mechanism and the absorption of^(3)He.And the provided source energy distribution in MCUCN is different from that in SFHe source.This study introduced enhancements to MCUCN to address these constraints,explicitly incorporating the^(4)He upscattering effect,the absorption of^(3)He,the loss caused by impurities on converter wall,UCN source energy distribution in SFHe,and the transmission through negative optical potential.Additionally,a Python-based visualization code for intermediate states and results was developed.To validate these enhancements,we systematically compared the simulation results of the Lujan Center Mark3 UCN system by MCUCN and the improved MCUCN code(iMCUCN)with UCNtransport simulations.Additionally,we compared the results of the SUN1 system simulated by MCUCN and iMCUCN with measurement results.The study demonstrates that iMCUCN effectively simulates the storage and transportation of ultracold neutrons in He-Ⅱ.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project No.PNURSP2025R510Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The technological advancement of the vehicular Internet ofThings(IoT)has revolutionized Intelligent Transportation Systems(ITS)into next-generation ITS.The connectivity of IoT nodes enables improved data availability and facilitates automatic control in the ITS environment.The exponential increase in IoT nodes has significantly increased the demand for an energy-efficient,mobility-aware,and secure system for distributed intelligence.This article presents a mobility-aware Deep Reinforcement Learning based Federated Learning(DRL-FL)approach to design an energy-efficient and threat-resilient ITS.In this approach,a Policy Proximal Optimization(PPO)-based DRL agent is first employed for adaptive client selection.Second,an autoencoder-based anomaly detectionmodule is considered for malicious node detection.Results reveal that the proposed framework achieved an 8%higher accuracy increase,and 15%lower energy consumption.Themodel also demonstrates greater resilience under adversarial conditions compared to the state of the art in federated learning.The adaptability of the proposed approach makes it a compelling choice for next-generation vehicular networks.
文摘Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.
基金funded by the Wuxi Young Scientific and Technological Talent Support Initiative,project number:TJXD-2024-203the Natural Science Foundation of the Jiangsu Higher Education Institutions of China,grant number:24KJB470027.
文摘Iterative Learning Control(ILC)provides an effective framework for optimizing repetitive tasks,making it particularly suitable for high-precision applications in both precision manufacturing and intelligent transportation systems(ITS).This paper presents a systematic review of ILC's developmental progress,current methodologies,and practical implementations across these two critical domains.The review first analyzes the key technical challenges encountered when integrating ILC into precision manufacturing workflows.Through case studies,it evaluates demonstrated improvements in positioning accuracy,surface finish quality,and production throughput.Furthermore,the study examines ILC’s applications in ITS,with particular focus on vehicular motion control applications including autonomous vehicle trajectory tracking,platoon coordination,and traffic signal timing optimization,where its data-driven characteristics enhance adaptability to dynamic environments.Finally,the paper proposes targeted future research directions that are essential for fully realizing ILC’s potential in advancing these interconnected yet distinct fields.
文摘As urbanization continues to accelerate,the challenges associated with managing transportation in metropolitan areas become increasingly complex.The surge in population density contributes to traffic congestion,impacting travel experiences and posing safety risks.Smart urban transportation management emerges as a strategic solution,conceptualized here as a multidimensional big data problem.The success of this strategy hinges on the effective collection of information from diverse,extensive,and heterogeneous data sources,necessitating the implementation of full⁃stack Information and Communication Technology(ICT)solutions.The main idea of the work is to investigate the current technologies of Intelligent Transportation Systems(ITS)and enhance the safety of urban transportation systems.Machine learning models,trained on historical data,can predict traffic congestion,allowing for the implementation of preventive measures.Deep learning architectures,with their ability to handle complex data representations,further refine traffic predictions,contributing to more accurate and dynamic transportation management.The background of this research underscores the challenges posed by traffic congestion in metropolitan areas and emphasizes the need for advanced technological solutions.By integrating GPS and GIS technologies with machine learning algorithms,this work aims to pay attention to the development of intelligent transportation systems that not only address current challenges but also pave the way for future advancements in urban transportation management.
基金Under the auspices of Heilongjiang Provincial Natural Science Foundation of China(No.YQ2024D012),National Natural Science Foundation of China(No.42071162,42101165,42501220)。
文摘Under the background of‘the Belt and Road’and‘China-Mongolia-Russia Economic Corridor’initiatives,this paper studied the urban accessibility level,regional accessibility pattern and regional spatial effects along the Primorsky No.1 and No.2 transportation corridors.First,the evaluation of urban accessibility level with and without Primorsky No.1 and No.2 high-speed rails(HSRs)opening was conducted with two indicators,i.e.,the weighted average travel time,and the economic potential.After the evaluation,the spatial differentiation pattern of the accessibility changes with and without Primorsky No.1 and No.2 HSRs opening was performed respectively using ArcGIS.On these bases,the regional spatial effects brought by Primorsky No.1 and No.2 HSRs opening were studied.The results are as following.First,the urban accessibility level will be greatly improved by the opening of Primorsky No.1 and No.2 HSRs.All adjacent cities will be integrated into‘1 h HSR communication circle’and the whole journey will be integrated into‘4 h HSR communication circle’along Primorsky No.1 and No.2 corridors,respectively.The HSR accessibility of Primorsky No.1 corridor is stronger than that of Primorsky No.2 corridor.But the HSR accessibility improvement degree of Primorsky No.1 corridor is weaker than that of Primorsky No.2 corridor.Second,spatially,along Primorsky No.1 and No.2 corridors,the HSR accessibility level of the cities which are located in China is stronger than those cities located in Russia,showing the‘High West,Low East’patterns.The HSR accessibility improvement degree of the cities which are located in Russia and Sino-Russian border is stronger than those cities located in China,showing the‘High East,Low West’patterns.Third,Primorsky No.1 and No.2 corridors could connect the China’s‘Heilongjiang Land Sea Silk Road Economic Belt’and‘Changchun-Jilin-Tumen Development Pilot Zone’respectively,gradually involving into the development of China’s Harbin-Changchun Megalopolis.Relying on Harbin(China)and Changchun(China),Primorsky No.1 and No.2 HSRs could connect Northeast China-Beijing HSR,accelerating the diffusion of population,economy and other flows from China’s Beijing-Tianjin-Hebei Urban Agglomeration to Northeast China,and then to Russia’s Far East Federal District.Relying on Suifenhe(China)and Hunchun(China),Primorsky No.1 and No.2 HSRs could be conducive to the development of the second largest sea channels for Northeast China,creating the Northeast Asian Urban Belt,and new sea-rail intermodal pattern among China,Russia,Democratic People’s Republic of Korea,Japan and Republic of Korea.Relying on Vladivostok(Russia)and Zarubino(Russia),Primorsky No.1 and No.2 corridors could connect the‘Ice Silk Road’,building the‘Sino-Russian Northern Maritime Corridor’and‘Sino-Russian Arctic Blue Economic Areas’.
文摘To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.
基金supported by National Key Research and Development Program of China(Grant No.2021YFE0115200)the Regional Innovation and Development Joint Fund of National Natural Science Foundation of China(Grant No.U22A20356).
文摘Solid lipid nanoparticles(SLN)could enhance the oral bioavailability of loaded protein and peptide drugs through lymphatic transport.Natural oligopeptides regulate nearly all vital processes and serve as a nitrogen source for nourishment.They are mainly transported by oligopeptide transporter-1(PepT-1)which are primarily expressed in the intestine with the characteristics of high-capacity and low energy consumption.Our preliminary research discovered the transmembrane transport of SLN could be improved by stimulating the oligopeptide absorption pathway.This implied the potential of combining the advantages of SLN with oligopeptide transporter mediated transportation.Herein,two kinds of dipeptide modified SLN were designed with insulin and glucagon like peptide-1(GLP-1)analogue exenatide as model drugs.These drugs loaded SLN showed enhanced oral bioavailability and hypoglycemic effect in both type I diabetic C57BL/6mice and type II diabetic KKAymice.Compared with un-modified SLN,dipeptide-modified SLN could be internalized by intestinal epithelial cells via PepT-1-mediated endocytosis with higher uptake.Interestingly,after internalization,more SLN could access the systemic circulation via lymphatic transport pathway,highlighting the potential to combine the oligopeptide-absorption route with SLN for oral drug delivery.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia through research group No.(RG-NBU-2022-1234).
文摘Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.
文摘Smart transportation is a key direction and trend in the development of China’s public transportation sector.Under this background,new opportunities for the development of transportation engineering education have emerged,necessitating the active promotion of hybrid teaching in transportation engineering courses.This approach aims to achieve innovation in teaching content and enhance the quality and effectiveness of education.Therefore,to improve the quality of transportation engineering education,this paper conducts research and exploration on the reform of hybrid teaching content.It proposes several measures,including constructing a dynamic teaching content system,strengthening faculty education and training,improving teaching facilities and technical support,and reinforcing students’self-discipline in learning.These initiatives aim to promote the reform of transportation engineering courses under the current smart transportation background and enhance the overall level and quality of education.
基金The 2024 Chongqing Municipal Education Commission Science and Technology Research Project,“Research on the Planning and Design of Modern Comprehensive Transportation Hubs under the Background of the Construction of the Chengdu-Chongqing Twin-City Economic Circle:A Case Study of Jinfeng Hub in Chongqing High-tech Zone”(Project No.:KJQN202405604).
文摘The Chengdu-Chongqing twin city economic circle has become a national strategy.As the westwards gateway of Chongqing central city,the High-tech Zone should further strengthen its traffic integration and interconnectivity with the Chengdu-Chongqing main Corridor.Combining the design concept and functional positioning of Jinfeng Hub,the research should be carried out from the aspects of hub scale control,three-dimensional spatial layout,rail transit connection,road collection and distribution system construction,and integrated development with the city.It is expected to provide a good reference for the planning and design of modern integrated transportation hub.
基金the financial support from the National Natural Science Foundation of China(Nos.52074176,52300165,52300056,52300099)Natural Science Foundation of Shandong Province Youth Project(No.ZR2022QB155)Open Project Program of Engineering Research Center of Groundwater Pollution Control and Remediation,Ministry of Education of China(No.GW202203)。
文摘Inactivation of carbon-based transition metal catalysts,which was caused by electron loss,limited their application in advanced oxidation processes.Therefore,Co and TiO_(2) double-loaded carbon nanofiber material(Co@CNFs-TiO_(2))was synthesized in this study.Photocatalytic and chemical catalytic systems were synergized efficiently.Tetracycline was eliminated within 15 min.The degradation rate remained above 90%after five cycles,and the 50%promotion proved the high stability of Co@CNFs-TiO_(2).The main reactive oxygen species in this system were sulfate radicals,whereas Co and TiO_(2) represented the active sites of the catalytic reaction.Electrons generated from TiO_(2) during the photocatalytic process were transferred to Co,which promoted the Co(Ⅲ)/Co(Ⅱ)cycle and maintained Co in a low-valence state,thereby stimulating the generation of sulfate radicals.In this study,the effective regulation of reactive oxygen species in the reaction system was realized.The results provided a guidance for in situ electron replenishment and regeneration of carbon-based transition metal catalysts,which will expand the practical application of advanced oxidation processes.
基金supported by the National Key R&D Program of China(no.2022YFB3803700)the National Natural Science Foundation(52401386)the SINOPEC Research Institute of Petroleum Processing Co.Ltd.Fund(25H010102119).
文摘Hydrogen,as a clean and versatile energy carrier,plays a vital role in the global transition toward carbon neutrality.Achieving a sustainable hydrogen economy requires safe,efficient,and cost‐effective technologies across production,storage,transportation,and utilization.On the production side,electrolysis and solar‐driven photocatalysis are rapidly advancing toward industrial adoption,yet remain constrained by electrolysis efficiency,cost,and electrolyzer durability.For storage and transportation,lowering costs and energy consumption,improving system efficiency,and deploying safe,high‐capacity hydrogen storage and transportation solutions are key priorities.Regarding hydrogen utilization,particularly hydrogen fuel cells and hydrogen‐based power systems,require further enhancement in their durability,reliability,and integration flexibility to enable widespread deployment across sectors.Therefore,this review provides a comprehensive overview of green hydrogen technologies,emphasizing recent advances,key challenges,and industrial demonstrations.By integrating insights from electrochemical and photochemical production,solid‐state and liquid‐phase storage,and hydrogen end‐use pathways,we propose a roadmap toward the scalable deployment of green hydrogen infrastructure.Coordinated progress across these domains will position hydrogen as a cornerstone of a sustainable,secure,and decarbonized global energy solution.
基金supported by the Yuxiu Innovation Project of NCUT(Grant No.2024NCUTYXCX211).
文摘Purpose–This paper aims to provide a comprehensive analysis of the strategic adjustments in China’s transportation structure,with a particular focus on the pivotal role of railway freight and its integration into the modern logistics system.It seeks to address the need for a more nuanced understanding of the“road to rail”policy,emphasizing the importance of intermodal collaboration and service of fragmented market demands.Design/methodology/approach–The study employs a transport economics perspective to evaluate the achievements and shortcomings of China’s transportation structure optimization.It bases its assessment of the current state of railway freight logistics,multi-modal transportation and the broader implications for the transportation service market on data analysis.The methodology includes a review of existing policies,an examination of industry practices and a comparative analysis with global trends in railway logistics.Findings–The research underscores the importance of focusing on the development of non-bulk materials,noting the insufficiency in the development of China’s rail multi-modal transportation and highlighting the instructive value of successful cases in open-top container road-rail intermodal transportation.The study posits that the railway sector must enhance cooperation with other market entities,aligning with the lead enterprises in the logistics chain that are characterized by speed,high value and strong coordination capabilities,in order to better serve the transportation market.This approach moves away from a reliance on the railway’s own capabilities alone.Originality/value–This paper offers original insights into the transformation of railway freight in China,contributing to the body of knowledge on transportation economics and logistics.It provides valuable recommendations for policymakers and industry practitioners,emphasizing the strategic importance of railway logistics in the context of China’s economic development and intense competition in the supply chain.The value of the article lies in its comprehensive understanding of the complexities involved in the adjustment of transportation structures,providing direction for the market-oriented reform of China’s railway freight sector.
基金support of this work by National Key Research and Development Program of China(2019YFC19059003)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(23KJB430024)+1 种基金Jiangsu Funding Program for Excellent Postdoctoral Talent(2023ZB680)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)are gratefully acknowledged.
文摘The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of managing personal moisture/thermal comfort in response to changing external environments remains a challenge.Herein,a smart cellulose-based Janus fabric was designed to dynamically manage personal moisture/heat.The cotton fabric was grafted with N-isopropylacrylamide to construct a temperature-stimulated transport channel.Subsequently,hydrophobic ethyl cellulose and hydrophilic cellulose nanofiber were sprayed on the bottom and top sides of the fabric to obtain wettability gradient.The fabric exhibits anti-gravity directional liquid transportation from hydrophobic side to hydrophilic side,and can dynamically and continuously control the transportation time in a wide range of 3–66 s as the temperature increases from 10 to 40℃.This smart fabric can quickly dissipate heat at high temperatures,while at low temperatures,it can slow down the heat dissipation rate and prevent the human from becoming too cold.In addition,the fabric has UV shielding and photodynamic antibacterial properties through depositing graphitic carbon nitride nanosheets on the hydrophilic side.This smart fabric offers an innovative approach to maximizing personal comfort in environments with significant temperature variations.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
基金supported by the National Natural Science Foundation of China(72022018,72091210)Youth Innovation Promotion Association,Chinese Academy of Sciences(2021454).
文摘With the maturation of emerging information technologies(Internet of Things,cloud computing,and big data),distributed manufacturing has emerged as an important model for future manufacturing.3D printing,with its integrated molding and design freedom,is a powerful catalyst for distributed manufacturing.This paper investigates the integrated production and transportation scheduling problem in distributed 3D printing.To solve this problem,we decompose the original problem into three sub-problems and design a multilevel optimization algorithm.We employ a genetic algorithm in the outer-level optimization to determine the optimal allocation of parts to machines.In the inner-level optimization,we utilize a simulated annealing algorithm to tackle the vehicle routing problem during the transportation stage followed by a local search algorithm to address the scheduling problem encountered during the production stage.Our algorithm is validated using real data from a 3D printing company,and the results show that our algorithm can obtain solutions that are the same as or better than those of Gurobi in a reasonable time for small-sized instances.Additionally,three types of initial methods are tested on large-sized instances to verify the efficiency of the proposed algorithm,and some interesting insights are also revealed and discussed.
