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Route optimization model for pedestrian evacuation in metro hubs 认领 引用 被引量：3
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作者 任刚 赵星 李岩 《Journal of Central South University》 SCIE EI CAS 2014年第2期822-831,共10页
The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedan... The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedance function for metro hubs which used the relationships among circulation speed,density and flow rate for pedestrians was defined.Then,a route optimization model which minimizes the movement time of the last evacuee was constructed to optimize evacuation performance.Solutions to the proposed mathematical model were obtained through an iterative optimization process.The route optimization model was applied to Xidan Station of Beijing Metro Line 4 based on the actual situations,and the calculation results of the model were tested using buildingExodus microscopic evacuation simulation software.The simulation result shows that the proposed model shortens the evacuation time by 16.05%,3.15% and 2.78% compared with all or none method,equally split method and Logit model,respectively.Furthermore,when the population gets larger,evacuation efficiency in the proposed model has a greater advantage. 展开更多
关键词 route optimization problem path impedance evacuation pedestrian flow metro hub
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Geographic Drone-based Route Optimization Approach for Emergency Area Ad-Hoc Network 认领 引用
2
作者 V.Krishnakumar R.Asokan 《Computer Systems Science & Engineering》 SCIE EI 2023年第4期985-1000,共16页
Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis.The recent challenges faced in Mobile Ad Hoc Networks(MANETs)include scalability,local... Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis.The recent challenges faced in Mobile Ad Hoc Networks(MANETs)include scalability,localization,heterogeneous network,self-organization,and self-sufficient operation.In this background,the current study focuses on specially-designed communication link establishment for high connection stability of wireless mobile sensor networks,especially in disaster area network.Existing protocols focus on location-dependent communications and use networks based on typically-used Internet Protocol(IP)architecture.However,IP-based communications have a few limitations such as inefficient bandwidth utilization,high processing,less transfer speeds,and excessive memory intake.To overcome these challenges,the number of neighbors(Node Density)is minimized and high Mobility Nodes(Node Speed)are avoided.The proposed Geographic Drone Based Route Optimization(GDRO)method reduces the entire overhead to a considerable level in an efficient manner and significantly improves the overall performance by identifying the disaster region.This drone communicates with anchor node periodically and shares the information to it so as to introduce a drone-based disaster network in an area.Geographic routing is a promising approach to enhance the routing efficiency in MANET.This algorithm helps in reaching the anchor(target)node with the help of Geographical Graph-Based Mapping(GGM).Global Positioning System(GPS)is enabled on mobile network of the anchor node which regularly broadcasts its location information that helps in finding the location.In first step,the node searches for local and remote anticipated Expected Transmission Count(ETX),thereby calculating the estimated distance.Received Signal Strength Indicator(RSSI)results are stored in the local memory of the node.Then,the node calculates the least remote anticipated ETX,Link Loss Rate,and information to the new location.Freeway Heuristic algorithm improves the data speed,efficiency and determines the path and optimization problem.In comparison with other models,the proposed method yielded an efficient communication,increased the throughput,and reduced the end-to-end delay,energy consumption and packet loss performance in disaster area networks. 展开更多
关键词 Mobile ad hoc networks(MANETs) geographical graph-based mapping(GGM) geographic drone based route optimization data speed anchor node’s
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Study on Rural Solid Waste Collection and Transportation Mode and Route Optimization Strategy in the Cold Regions of Northern China 认领 引用
3
作者 Li Chuan-gang Liu Peng +1 位作者 Xu Hui Ma Li 《Journal of Northeast Agricultural University(English Edition)》 CAS 2023年第4期75-88,共14页
Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and tran... Rural vitalization is a major strategy for reform and development of agriculture and rural areas in China,the key task of which is improving rural living environment.Imperfect rural solid waste(RSW)collection and transportation system exacerbates the pollution of RSW to rural living environment,while it has not been established and improved in the cold region of Northern China due to climate and economy.Through the analysis of the current situation of RSW source separation,collection,transportation and disposal in China,an RSW collection and transportation system suitable for the northern cold region was developed.Considering the low winter temperature in the northern cold region,different requirements for RSW collection,transportation and terminal disposal,scattered source points and single terminal disposal nodes in rural areas,the study focused on determining the number and location of transfer stations,established a model for transfer stations selection and RSW collection and transportation routes optimization for RSW collection and transportation system,and proposed the elite retention particle swarm optimization–genetic algorithm(ERPSO–GA).The rural area of Baiquan County was taken as a representative case,the collection and transportation scheme of which was given,and the feasibility of the scheme was clarified by simulation experiment. 展开更多
关键词 rural solid waste(RSW) collection and transportation route optimization rural environment collection and transportation costs elite retention particle swarm optimization-genetic algorithm(ERPSO-GA)
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The Impact of Rural Electricity Supplier on Resettlement of Rural Surplus Labor Force and the Route Optimization 认领 引用
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作者 MA Jinhai 《International English Education Research》 2016年第1期47-50,共4页
Based on the perspective of electricity supplier on the issues of Rural Surplus Labor resettlement, we analyzed China＇s rural electricity supplier development and resettlement of rural surplus labor issues and factor... Based on the perspective of electricity supplier on the issues of Rural Surplus Labor resettlement, we analyzed China＇s rural electricity supplier development and resettlement of rural surplus labor issues and factors, proposed the impact of sluggish development of rural electricity suppliers on their resettlement of the rural surplus labor force, and made the following suggestions： to develop township enterprises, to strengthen the construction of small towns, to settlement surplus labor force on the post, to transfer the surplus labor, to increase farmers＇ income; to eliminate the urban-rural dual structure, to implement loose household registration management system, to increase education level, to improve the quality of farmers, to provide information and improve guidance to change disorderly transfer to the orderly transfer. 展开更多
关键词 Rural Electricity Supplier Rural Surplus Labor Force Resettlement Route Optimization
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Application of drones in issuing parking tickets:an innovative solution for route optimization and workforce replacement 认领 引用
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作者 Shih-Hao Lu Chia-Chen Chang +1 位作者 Rohit Raj Wei-Tsung Lai 《International Journal of Intelligent Computing and Cybernetics》 EI 2025年第4期812-855,共44页
Purpose–With the rapid advancement of drone technology,its application scope and potential are expected to grow substantially in the future.Currently,urban parking enforcement predominantly relies on traditional manu... Purpose–With the rapid advancement of drone technology,its application scope and potential are expected to grow substantially in the future.Currently,urban parking enforcement predominantly relies on traditional manual operations,where personnel patrol on motorcycles to issue parking tickets and collect fees.However,this approach faces significant challenges in efficiency and resource allocation,especially amidst growing labor shortages.To address these issues,this study proposes an innovative and efficient solution:utilizing drone technology to replace traditional manual parking enforcement.Design/methodology/approach–The research focuses on optimizing routes,determining charging station placement and analyzing operational costs.Using real parking data from New Taipei City,this study conducts simulations to evaluate three routing strategies:road-based,non-road-based and automated clustering.The goal is to identify the most efficient and feasible drone routing strategy for urban parking enforcement.Additionally,the study examines the effects of single versus multiple charging station layouts on operational outcomes,offering valuable insights for practical implementation.Findings–The experimental results demonstrate that drones significantly reduce total route distances,energy consumption and operational costs.In high-,medium-and low-density parking areas,automated routing strategies that combine K-means clustering with nearest-neighbor algorithms effectively balance workload distribution and minimize flight time.Moreover,the findings reveal that positioning charging stations in overlapping gray zones enhances route efficiency while reducing infrastructure costs.Originality/value–This research provides an innovative framework for drone-based parking management,laying a solid foundation for integrating emerging technologies into smart city management.Furthermore,the proposed drone-based enforcement approach achieves substantial benefits in energy efficiency and operational costs,with potential cost reductions of up to 90%compared to traditional manual enforcement strategies. 展开更多
关键词 Vehicle routing problem Drone technology Route optimization Nearest neighbor algorithm Drone-assisted parking management
Enhancing Urban Rail Transit Train Routes Planning Using Surrogate-Assisted Fish Migration Optimization 认领 引用
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作者 Zhigang Du Jengshyang Pan +2 位作者 Xiaoyang Wang Shuchuan Chu Shaoquan Ni 《Journal of Bionic Engineering》 SCIE EI CSCD 2025年第4期1702-1716,共15页
Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which c... Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios. 展开更多
关键词 Train routing optimization Surrogate-assisted Fish migration optimization Meta-heuristic evolutionary algorithm
Optimization of integrated resource utilization in railway hubs with mixed high-speed and conventional operations at shared stations 认领 引用
7
作者 Sitong Xiang Feng Lin +2 位作者 Zhigang Le Datong Song Ershuai Nie 《Railway Sciences》 2026年第4期489-504,共16页
Purpose-With the continuous expansion of railway hubs,increasing functional complexity and growing capacity constraints,the coordinated and efficient utilization of transportation resources-such as stations,lines and ... Purpose-With the continuous expansion of railway hubs,increasing functional complexity and growing capacity constraints,the coordinated and efficient utilization of transportation resources-such as stations,lines and maintenance facilities-has become a critical issue for improving hub operational efficiency.This study focuses on the division of functions within railway hubs that incorporate shared stations operating under mixed high-speed and conventional train services.Design/methodology/approach-An optimization model for hub functional allocation is developed to achieve efficient resource utilization in hubs containing mixed-operation stations.A node-arc network representation combined with an improved multi-commodity flow model is employed,taking train dwell and operation time within the hub as the optimization objective.A case study is conducted to derive optimized solutions,followed by both qualitative and quantitative analyses.Findings-The results indicate that optimizing train operation routes and station assignments within the hub can effectively reduce the total occupation time of train flows and significantly improve resource utilization efficiency.Originality/value-The proposed model demonstrates both scientific rigor and practical effectiveness.In realworld operations,it can provide operators with preliminary and proactive functional allocation schemes,help identify key constraints limiting hub capacity utilization and offer decision support for transport plan adjustments or infrastructure and facility upgrades. 展开更多
关键词 Mixed high-speed and conventional operations Railway hub Hub functional allocation Route optimization ILOG CPLEX
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ROAD+:Route Optimization with Additional Destination-Information and Its Mobility Management in Mobile Networks 认领 引用
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作者 Moonseong Kim Matt W.Mutka +1 位作者 Jeonghoon Park Hyunseung Choo 《Journal of Computer Science & Technology》 SCIE EI 2010年第2期298-312,共15页
In the NEtwork MObility(NEMO)environment,mobile networks can form a nested structure.In nested mobile networks that use the NEMO Basic Support(NBS)protocol,pinball routing problems occur because packets are routed to ... In the NEtwork MObility(NEMO)environment,mobile networks can form a nested structure.In nested mobile networks that use the NEMO Basic Support(NBS)protocol,pinball routing problems occur because packets are routed to all the home agents of the mobile routers using nested tunneling.In addition,the nodes in the same mobile networks can communicate with each other regardless of Internet connectivity.However,the nodes in some mobile networks that are based on NBS cannot communicate when the network is disconnected from the Internet.In this paper,we propose a route optimization scheme to solve these problems.We introduce a new IPv6 routing header named"destination-information header"(DH),which uses DH instead of routing header type 2 to optimize the route in the nested mobile network.The proposed scheme shows at least 30%better performance than ROTIO and similar performance improvement as DBU in inter-route optimization.With respect to intra-route optimization,the proposed scheme always uses the optimal routing path.In addition,the handover mechanism in ROAD+outperforms existing schemes and is less sensitive to network size than other existing schemes. 展开更多
关键词 NEtwork MObility(NEMO) route optimization(RO) NEMO basic support(NBS) pinball routing problem mobile network nested mobile network
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Air route network optimization in fragmented airspace based on cellular automata 认领 引用 被引量：25
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作者 Shijin WANG Xi CAO +3 位作者 Haiyun LI Qingyun LI Xu HANG Yanjun WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2017年第3期1184-1195,共12页
Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has ... Air route network optimization,one of the essential parts of the airspace planning,is an effective way to optimize airspace resources,increase airspace capacity,and alleviate air traffic congestion.However,little has been done on the optimization of air route network in the fragmented airspace caused by prohibited,restricted,and dangerous areas（PRDs）.In this paper,an air route network optimization model is developed with the total operational cost as the objective function while airspace restriction,air route network capacity,and non-straight-line factors（NSLF） are taken as major constraints.A square grid cellular space,Moore neighbors,a fixed boundary,together with a set of rules for solving the route network optimization model are designed based on cellular automata.The empirical traffic of airports with the largest traffic volume in each of the 9 flight information regions in China's Mainland is collected as the origin-destination（OD） airport pair demands.Based on traffic patterns,the model generates 35 air routes which successfully avoids 144 PRDs.Compared with the current air route network structure,the number of nodes decreases by 41.67%,while the total length of flight segments and air routes drop by 32.03% and 5.82% respectively.The NSLF decreases by 5.82% with changes in the total length of the air route network.More importantly,the total operational cost of the whole network decreases by 6.22%.The computational results show the potential benefits of the model and the advantage of the algorithm.Optimization of air route network can significantly reduce operational cost while ensuring operation safety. 展开更多
关键词 Air route network planning Airspace restriction Cellular automata Network capacity Optimization of nodes
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Strategic Assessment of Sustainable Marine Logistics in Arctic Routes Using Resilient and Agile Supply Chain Theory 认领 引用
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作者 Suleiman Ibrahim Mohammad Sultan Alaswad Alenazi +2 位作者 Asokan Vasudevan Hanan Jadallah Badrea Al Oraini 《Sustainable Marine Structures》 2025年第4期84-103,共20页
The rapid transformation of Arctic maritime routes,driven by diminishing sea ice and shifting geopolitical conditions,presents both opportunities and challenges for global shipping.This study develops an integrated op... The rapid transformation of Arctic maritime routes,driven by diminishing sea ice and shifting geopolitical conditions,presents both opportunities and challenges for global shipping.This study develops an integrated optimization framework for sustainable Arctic marine logistics,grounded in Agile Supply Chain Theory(ASCT),to address cost efficiency,environmental sustainability,and operational robustness under climate and policy uncertainty.A Mixed‐Integer Linear Programming(MILP)model was employed to optimize vessel routing across Arctic corridors,incorporating Energy Efficiency Operational Indicator(EEOI)and Carbon Intensity Indicator(CII)metrics directly into the objective function.Scenario analyses tested performance under varying climate conditions and policy constraints.The model was parameterized using vessel operational data from Arctic shipping logs,environmental datasets from ESA CryoSat‐2 and NSIDC,port accessibility records from Arctic port authorities,and economic data from Clarksons and the World Bank,ensuring realistic and replicable inputs for the analysis.Results demonstrate that ASCT‐based optimized routes achieved an average 14.8%reduction in operating costs,12.3%reduction in CO₂emissions,and an 11.6%improvement in EEOI,with the majority of voyages improving by at least one CII grade.Robustness analysis showed that optimized routes maintained up to 14.7 percentage points higher feasibility under severe ice scenarios and reduced cost volatility by 20–28%under carbon tax regimes.These findings confirm the value of embedding agility and resilience principles into Arctic shipping,aligning operational efficiency with International Maritime Organization(IMO)decarbonization objectives.The study extends ASCT into extreme maritime contexts,offering a replicable model for sustainable route planning in high‐risk logistics sectors. 展开更多
关键词 Arctic Shipping Route Optimization Agile Supply Chain Theory MILP,Resilience Sustainability EEOI CII
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Optimization Route Algorithm Based on the Minimal Transfer Time and Distance 认领 引用
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作者 胡红萍 赵敏 白艳萍 《Journal of Measurement Science and Instrumentation》 CAS 2011年第4期333-336,共4页
The transfer system,an important subsystem in urban citizen passenger transport system,is a guarantee of public transport priority and is crucial in the whole urban passenger transport traffic.What the majority of bus... The transfer system,an important subsystem in urban citizen passenger transport system,is a guarantee of public transport priority and is crucial in the whole urban passenger transport traffic.What the majority of bus passengers consider is the convenience and comfort of the bus ride,which reduces the transfer time of bus passengers."Transfer time" is considered to be the first factor by the majority of bus passengers who select the routes.In this paper,according to the needs of passengers,optimization algorithm,with the minimal distance being the first goal,namely,the improved Dijkstra algorithm based on the minimal distance,is put forward on the basis of the optimization algorithm with the minimal transfer time being the first goal. 展开更多
关键词 transfer distance optimization route
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Optimization of Route Repair in Mobile Ad-hoc Network 认领 引用
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作者 李承 汪为农 《Journal of Shanghai University(English Edition)》 2004年第2期169-176,共8页
A main shortcoming of mobile Ad-hoc network's reactive routing protocols is the large volume of far-reaching control traffic required to support the route discovery (RD) and route repair (RR) mechanism. Using a ra... A main shortcoming of mobile Ad-hoc network's reactive routing protocols is the large volume of far-reaching control traffic required to support the route discovery (RD) and route repair (RR) mechanism. Using a random mobility model, this paper derives the probability equation of the relative distance (RDIS) between any two mobile hosts in an ad-hoc network. Consequently, combining with average equivalent hop distance (AEHD), a host can estimate the routing hops between itself and any destination host each time the RD/RR procedure is triggered, and reduce the flooding area of RD/RR messages. Simulation results show that this optimized route repair (ORR) algorithm can significantly decrease the communication overhead of RR process by about 35%. 展开更多
关键词 mobile ad-hoc network mobility model routing protocol optimized routing repair
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Optimization of Planning Routes in Solid Waste Collection 认领 引用
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作者 Thelma Pretel Brandao Vecchit Luiz Mario de Matos Jorge +1 位作者 Mauro Antonio da Silva Sá Ravagnani Paulo Roberto Paraíso 《Journal of Chemistry and Chemical Engineering》 2014年第6期596-601,共6页
This paper presents an optimization model for solving the planning problem of collection and transportation of solid waste in medium-sized cities. As final results, are expected to promote cost savings to the public c... This paper presents an optimization model for solving the planning problem of collection and transportation of solid waste in medium-sized cities. As final results, are expected to promote cost savings to the public coffers, as well as environmental benefits. The developed mathematical model is formulated as a problem of linear programming with mixed-integer variables and transcribed into software GAMS （general algebraic modeling system）. The practical application was tested using data collected in the central region of a Brazilian city with approximately 90,000 inhabitants. The deterministic model used allowed an optimal solution. It was found after inclusion of restrictions that eliminated the appearance of sub-routes. It was concluded that the optimal routes allow for a 38% reduction in total distance traveled, which can generate savings of $320.00 per day regarding maintenance and fuel trucks. 展开更多
关键词 Route optimization solid waste collection vehicle routing problem.
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Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm 认领 引用 被引量：11
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作者 Wang Shijin Li Qingyun +1 位作者 Cao Xi Li Haiyun 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2016年第4期469-478,共10页
Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective funct... Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%. 展开更多
关键词 air route network planning three area avoidance optimization of air route network node adaptive ant colony algorithm grid environment
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Dual objective multimodal transportation path optimization based on different carbon tax mechanisms under uncertain demand 认领 引用
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作者 Xu Zhang Hongzhu Chen +1 位作者 Haiyan Zhang Xumei Yuan 《Journal of Highway and Transportation Research and Development(English Edition)》 2025年第1期52-60,共9页
By delving into low-carbon transportation research,we can address the imperative for the high-quality development of transportation services,while simultaneously advancing the realization of the dual-carbon objective.... By delving into low-carbon transportation research,we can address the imperative for the high-quality development of transportation services,while simultaneously advancing the realization of the dual-carbon objective.This study focuses on optimizing multimodal transport routes under varying carbon tax frameworks,taking into account the demand uncertainty that arises from unforeseen events such as abrupt restocking or seasonal fluctuations.We formulate a dual-objective 0-1 path optimization model under both a unified carbon tax mechanism and a piecewise progressive carbon tax scheme.The model aims to minimize total cost and carbon emissions in the face of stochastic demand.Utilizing Monte Carlo simulation and the laws of large numbers,we convert the model to maximize the expected value of the uncertain objective.An enhanced non-dominated sorting genetic algorithm is then developed to solve this model,yielding solutions that more effectively meet our objectives.This algorithm is designed to expand the search space,mitigating the""premature convergence"issue and thereby generating superior individuals and solutions.Finally,we assess the applicability of our model and algorithm to transportation challenges within the context of the dual-carbon initiative through a numerical example.We also explore the influence of different carbon tax mechanisms on total cost and emissions,as well as their applicability and efficacy in the face of demand uncerainty.The findings indicate that companies can achieve emission reductions with minimal cost increases under dual-target cost scenarios,ideal for dual carbon transportation contexts.Moreover,carbon tax rates significantly impact emission control,with segmented progressive taxes proving more effective,especially in high-demand uncertainty.Decisionmakers should consider technological capabilities to set optimal tax rates and thresholds,fostering corporate enthusiasm.This research informs policy and decision-making for authorities and firms. 展开更多
关键词 Transport economics Dual-objective route optimization Improved non-dominated sorting genetic algorithm Multimodal transport Demand uncertainty Carbon tax mechanism
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Optimizing Routing Algorithms for Next-Generation Networks:A Resilience-Driven Framework for Space-Air-Ground Integrated Networks 认领 引用
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作者 Peiying Zhang Yihong Yu +3 位作者 Jia Luo Nguyen Gia Ba Lizhuang Tan Lei Shi 《Computers, Materials & Continua》 SCIE EI 2026年第5期1177-1190,共14页
Next-GenerationNetworks(NGNs)demand high resilience,dynamic adaptability,and efficient resource utilization to enable ubiquitous connectivity.In this context,the Space-Air-Ground Integrated Network(SAGIN)architecture ... Next-GenerationNetworks(NGNs)demand high resilience,dynamic adaptability,and efficient resource utilization to enable ubiquitous connectivity.In this context,the Space-Air-Ground Integrated Network(SAGIN)architecture is uniquely positioned to meet these requirements.However,conventional NGN routing algorithms often fail to account for SAGIN’s intrinsic characteristics,such as its heterogeneous structure,dynamic topology,and constrained resources,leading to suboptimal performance under disruptions such as node failures or cyberattacks.To meet these demands for SAGIN,this study proposes a resilience-oriented routing optimization framework featuring dynamic weighting and multi-objective evaluation.Methodologically,we define three core routing performance metrics,quantified through a four-dimensionalmodel,encompassing robustness Rd,resilience Rr,adaptability Ra,and resource utilization efficiency Ru,and integrate them into a comprehensive evaluation metric.In simulated SAGIN environments,the proposed Multi-Indicator Weighted Resilience Evaluation Algorithm(MIW-REA)demonstrates significant improvements in resilience enhancement,recovery acceleration,and resource optimization.It maintains 82.3%service availability even with a 30%node failure rate,reduces Distributed Denial of Service(DDoS)attack recovery time by 43%,decreases bandwidth waste by 23.4%,and lowers energy consumption by 18.9%.By addressing challenges unique to the SAGIN network,this research provides a flexible real-time solution for NGN routing optimization that balances resilience,efficiency,and adaptability,advancing the field. 展开更多
关键词 Space-air-ground integrated network next-generation networks routing optimization resiliencedriven routing dynamic weighting multi-metric assessment
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Optimizing Cold Chain Logistics for Plateau Specialty Agricultural Products under the Company-Farmer Order Model 认领 引用
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作者 Siwen Wu Xiaoyan Yan 《Proceedings of Business and Economic Studies》 2026年第5期9-15,共7页
Plateau specialty agricultural products are constrained by long transport distances,unstable temperature control,weak rural logistics infrastructure,and fragmented smallholder production.This paper reframes cold chain... Plateau specialty agricultural products are constrained by long transport distances,unstable temperature control,weak rural logistics infrastructure,and fragmented smallholder production.This paper reframes cold chain logistics under the company-farmer order model as an integrated problem of route optimization,temperature-risk control,and contract coordination.Based on a literature review and a case-based scenario reconstructed from a plateau agricultural supply chain,the study proposes a compact optimization framework that incorporates transport cost,delivery time,vehicle capacity,cold-chain loss,weather and road risk,and allowable temperature fluctuation.The scenario comparison indicates that optimized routing and digital temperature monitoring may reduce transport cost from 5,000 to 4,000 RMB per ton,shorten delivery time from 48 to 36 hours,reduce temperature-related loss from 10%to 5%,increase transport efficiency from 80%to 95%,and lower risk frequency from 15%to 8%.The results suggest that cold chain upgrading in plateau areas should not be treated as a purely technical routing problem.It requires coordinated investment in refrigerated infrastructure,information sharing between firms and farmers,incentive-compatible order contracts,and public support for rural logistics platforms.The paper contributes a policy-oriented analytical framework for improving agricultural supplychain resilience in geographically disadvantaged plateau regions. 展开更多
关键词 Company-farmer model Plateau agriculture Cold chain logistics Route optimization Rural development
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QoS Routing Optimization Based on Deep Reinforcement Learning in SDN 认领 引用 被引量：4
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作者 Yu Song Xusheng Qian +2 位作者 Nan Zhang Wei Wang Ao Xiong 《Computers, Materials & Continua》 SCIE EI 2024年第5期3007-3021,共15页
To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront thechallenge of managing the surging demand for data traffic. Within this realm, the network imposes stringentQu... To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront thechallenge of managing the surging demand for data traffic. Within this realm, the network imposes stringentQuality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanismsin accommodating such extensive data flows. In response to the imperative of handling a substantial influx of datarequests promptly and alleviating the constraints of existing technologies and network congestion, we present anarchitecture forQoS routing optimizationwith in SoftwareDefinedNetwork (SDN), leveraging deep reinforcementlearning. This innovative approach entails the separation of SDN control and transmission functionalities, centralizingcontrol over data forwardingwhile integrating deep reinforcement learning for informed routing decisions. Byfactoring in considerations such as delay, bandwidth, jitter rate, and packet loss rate, we design a reward function toguide theDeepDeterministic PolicyGradient (DDPG) algorithmin learning the optimal routing strategy to furnishsuperior QoS provision. In our empirical investigations, we juxtapose the performance of Deep ReinforcementLearning (DRL) against that of Shortest Path (SP) algorithms in terms of data packet transmission delay. Theexperimental simulation results show that our proposed algorithm has significant efficacy in reducing networkdelay and improving the overall transmission efficiency, which is superior to the traditional methods. 展开更多
关键词 Deep reinforcement learning SDN route optimization QoS
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Load Balancing-Based Routing Optimization Mechanism for Power Communication Networks 认领 引用 被引量：14
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作者 Ningzhe Xing Siya Xu +1 位作者 Sidong Zhang Shaoyong Guo 《China Communications》 SCIE CSCD 2016年第8期169-176,共8页
In power communication networks,it is a challenge to decrease the risk of different services efficiently to improve operation reliability.One of the important factor in reflecting communication risk is service route d... In power communication networks,it is a challenge to decrease the risk of different services efficiently to improve operation reliability.One of the important factor in reflecting communication risk is service route distribution.However,existing routing algorithms do not take into account the degree of importance of services,thereby leading to load unbalancing and increasing the risks of services and networks.A routing optimization mechanism based on load balancing for power communication networks is proposed to address the abovementioned problems.First,the mechanism constructs an evaluation model to evaluate the service and network risk degree using combination of devices,service load,and service characteristics.Second,service weights are determined with modified relative entropy TOPSIS method,and a balanced service routing determination algorithm is proposed.Results of simulations on practical network topology show that the mechanism can optimize the network risk degree and load balancing degree efficiently. 展开更多
关键词 power communication networks load balancing routing optimization
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Multi-Hop Routing Optimization Method Based on Improved Ant Algorithm for Vehicle to Roadside Network 认领 引用 被引量：2
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作者 Hao Dong Xiaohui Zhao +2 位作者 Liangdong Qu Xuefen Chi Xinyu Cui 《Journal of Bionic Engineering》 SCIE EI CSCD 2014年第3期490-496,共7页
This paper proposes a route optimization method to improve the performance of route selection in Vehicle Ad-hoc Network(VANET).A novel bionic swarm intelligence algorithm,which is called ant colony algorithm,was intro... This paper proposes a route optimization method to improve the performance of route selection in Vehicle Ad-hoc Network(VANET).A novel bionic swarm intelligence algorithm,which is called ant colony algorithm,was introduced into a traditional ad-hoc route algorithm named AODV.Based on the analysis of movement characteristics of vehicles and according to the spatial relationship between the vehicles and the roadside units,the parameters in ant colony system were modified to enhance the performance of the route selection probability rules.When the vehicle moves into the range of several different roadsides,it could build the route by sending some route testing packets as ants,so that the route table can be built by the reply information of test ants,and then the node can establish the optimization path to send the application packets.The simulation results indicate that the proposed algorithm has better performance than the traditional AODV algorithm,especially when the vehicle is in higher speed or the number of nodes increases. 展开更多
关键词 multi-hop routing optimization ant colony algorithm VANET bionic swarm intelligence algorithm
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