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
An efficient parallel global router using random optimization that is independent of net ordering is proposed.Parallel approaches are described and strategies guaranteeing the routing quality are discussed.The wire le...An efficient parallel global router using random optimization that is independent of net ordering is proposed.Parallel approaches are described and strategies guaranteeing the routing quality are discussed.The wire length model is implemented on multiprocessor,which enables the algorithm to approach feasibility of large scale problems.Timing driven model on multiprocessor and wire length model on distributed processors are also presented.The parallel algorithm greatly reduces the run time of routing.The experimental results show good speedups with no degradation of the routing quality.展开更多
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
In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorith...In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing.The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area.Then,the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission.Relay nodes are selected layer by layer,starting from the outermost cluster heads.Finally,the inter-layer routing mechanism is integrated with regional partitioning and clustering methods to develop the WRSN energy optimization algorithm.To further optimize the algorithm’s performance,we conduct parameter optimization experiments on the relay routing selection function,cluster head rotation energy threshold,and inter-layer relay structure selection,ensuring the best configurations for energy efficiency and network lifespan.Based on these optimizations,simulation results demonstrate that the proposed algorithm outperforms traditional forward routing,K-CHRA,and K-CLP algorithms in terms of node mortality rate and energy consumption,extending the number of rounds to 50%node death by 11.9%,19.3%,and 8.3%in a 500-node network,respectively.展开更多
Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectu...Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.展开更多
A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is...A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is implemented and the global router is called CEE Gr.The CEE Gr is tested on MCNC benchmarks and the experimental results are promising.展开更多
Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimiz...Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimization of multiple Crossing Waypoints(CWPs)in the fragmented airspace separated by Prohibited,Restricted and Dangerous areas(PRDs).To tackle this issue,this paper proposes an Artificial Potential Field(APF)model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles.An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs,air route segments and PRDs.Based on the framework,an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost.The proposed model is applied to a busy controlled airspace.And the obtained results show that after optimization the safety-related indicators:conflict number and controller workload reduced by 7.75%and 6.51%respectively.As for the cost-effectiveness indicators:total route length,total air route cost and non-linear coefficient,declined by 1.74%,3.13%and 1.70%respectively.While the predictability indicator,total flight delay,saw a notable reduction by 7.96%.The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.展开更多
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
Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization mode...Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.展开更多
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
According to the characteristics and requirements of urban vegetable logistics and distribution, the optimization model is established to achieve the minimum distribution cost of distribution center. The algorithm of ...According to the characteristics and requirements of urban vegetable logistics and distribution, the optimization model is established to achieve the minimum distribution cost of distribution center. The algorithm of artificial bee colony is improved, and the algorithm based on MATLAB software is designed to solve the model successfully. At the same time, combined with the actual case, the two algorithms are compared to verify the effectiveness of the improved artificial bee colony algorithm in the optimization of urban vegetable distribution path.展开更多
AGRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation.One of the worst natural calamities that can disrupt a ship’s n...AGRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation.One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon.Currently,the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise.The distribution of heavy winds andwaves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution,which significantly enhances the challenge of the captain’s preparation for avoiding typhoon navigation.It is now necessary to find a solution to the challenge of designing a highsafety and effective ship navigation path to avoid typhoons.The T_GRASP algorithm is suggested to optimize the candidate set’s structure based on the GRASP algorithm’s frame.The algorithm can guarantee the safety of the ship to avoid typhoons and assure high route efficiency by using the lowest risk function,the shortest sailing time,and the least fuel consumption as the objective functions and the ship speed and highest safety as the model constraints.The outcomes of the simulation demonstrate the superiority of the suggested T_GRASP algorithm over both the conventional A∗algorithm and the ant colony algorithm.In addition to addressing issues with the traditional A∗algorithm,like its wide search space and poor efficiency,the proposed algorithm also addresses issues with the ant colony algorithm,like its excessive iterations and sluggish convergence.展开更多
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
The future aeronautical network will be based on IPv6 and the services over the aeronautical network will be classified into 3 domains: Air Traffic Services (ATS), Airline Operational Services (AOS) and Passenger Info...The future aeronautical network will be based on IPv6 and the services over the aeronautical network will be classified into 3 domains: Air Traffic Services (ATS), Airline Operational Services (AOS) and Passenger Information and Entertainment Services (PIES), among which the ATS and AOS domains are important for aircraft safety and airline business operation. Some schemes have been proposed to provide IP mobility support for aeronautical network, and Network Mobility (NEMO) scheme is the most promising one. However, using NEMO technology will lead to sub-optimal routing, so route optimization technology is highly desired for NEMO. A route optimization scheme is proposed for the ATS and AOS domains, which introduces the Correspondent Routers to realize the optimal routing and employs an improved procedure to reduce the handoff delay. The route optimization for the PIES domain is also discussed to provide better performance for some special scenarios.展开更多
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
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
The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and G...The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.展开更多
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
In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the disco...In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.展开更多
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
基金supported by the National Natural Science Foundation of China(Project No.52172321,52102391)Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)+1 种基金China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘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.
文摘An efficient parallel global router using random optimization that is independent of net ordering is proposed.Parallel approaches are described and strategies guaranteeing the routing quality are discussed.The wire length model is implemented on multiprocessor,which enables the algorithm to approach feasibility of large scale problems.Timing driven model on multiprocessor and wire length model on distributed processors are also presented.The parallel algorithm greatly reduces the run time of routing.The experimental results show good speedups with no degradation of the routing quality.
基金supported by the the Youth Science and Technology Innovation Fund (Science)(Nos.NS2014070, NS2014070)
文摘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%.
基金funded by National Natural Science Foundation of China(No.61741303)Guangxi Natural Science Foundation(No.2017GXNSFAA198161)the Foundation Project of Guangxi Key Laboratory of Spatial Information and Mapping(No.21-238-21-16).
文摘In large-scaleWireless Rechargeable SensorNetworks(WRSN),traditional forward routingmechanisms often lead to reduced energy efficiency.To address this issue,this paper proposes a WRSN node energy optimization algorithm based on regional partitioning and inter-layer routing.The algorithm employs a dynamic clustering radius method and the K-means clustering algorithm to dynamically partition the WRSN area.Then,the cluster head nodes in the outermost layer select an appropriate layer from the next relay routing region and designate it as the relay layer for data transmission.Relay nodes are selected layer by layer,starting from the outermost cluster heads.Finally,the inter-layer routing mechanism is integrated with regional partitioning and clustering methods to develop the WRSN energy optimization algorithm.To further optimize the algorithm’s performance,we conduct parameter optimization experiments on the relay routing selection function,cluster head rotation energy threshold,and inter-layer relay structure selection,ensuring the best configurations for energy efficiency and network lifespan.Based on these optimizations,simulation results demonstrate that the proposed algorithm outperforms traditional forward routing,K-CHRA,and K-CLP algorithms in terms of node mortality rate and energy consumption,extending the number of rounds to 50%node death by 11.9%,19.3%,and 8.3%in a 500-node network,respectively.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2023-2-02038).
文摘Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.
文摘A global routing algorithm with performance optimization under multi constraints is proposed,which studies RLC coupling noise,timing performance,and routability simultaneously at global routing level.The algorithm is implemented and the global router is called CEE Gr.The CEE Gr is tested on MCNC benchmarks and the experimental results are promising.
基金the Civil Aviation Authority of Singapore and the Nanyang Technological University,Singapore under their collaboration in the Air Traffic Management Research Institute。
文摘Air route crossing waypoint optimization is one of the effective ways to improve airspace utilization,capacity and resilience in dealing with air traffic congestion and delay.However,research is lacking on the optimization of multiple Crossing Waypoints(CWPs)in the fragmented airspace separated by Prohibited,Restricted and Dangerous areas(PRDs).To tackle this issue,this paper proposes an Artificial Potential Field(APF)model considering attractive forces produced by the optimal routes and repulsive forces generated by obstacles.An optimization framework based on the APF model is proposed to optimize the different airspace topologies varying the number of CWPs,air route segments and PRDs.Based on the framework,an adaptive method is developed to dynamically control the optimization process in minimizing the total air route cost.The proposed model is applied to a busy controlled airspace.And the obtained results show that after optimization the safety-related indicators:conflict number and controller workload reduced by 7.75%and 6.51%respectively.As for the cost-effectiveness indicators:total route length,total air route cost and non-linear coefficient,declined by 1.74%,3.13%and 1.70%respectively.While the predictability indicator,total flight delay,saw a notable reduction by 7.96%.The proposed framework and methodology can also provide an insight in the understanding of the optimization to other network systems.
基金co-supported by the National Natural Science Foundation of China(No.61304190)the Natural Science Foundation of Jiangsu Province(No.BK20130818)the Fundamental Research Funds for the Central Universities of China(No.NJ20150030)
文摘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.
基金Project(2009AA11Z220)supported by National High Technology Research and Development Program of ChinaProjects(61070112,61070116)supported by the National Natural Science Foundation of China+1 种基金Project(2012LLYJTJSJ077)supported by the Ministry of Public Security of ChinaProject(KYQD14003)supported by Tianjin University of Technology and Education,China
文摘Unmanned aerial vehicle(UAV)was introduced to take road segment traffic surveillance.Considering the limited UAV maximum flight distance,UAV route planning problem was studied.First,a multi-objective optimization model of planning UAV route for road segment surveillance was proposed,which aimed to minimize UAV cruise distance and minimize the number of UAVs used.Then,an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV route planning problem.At last,a UAV flight experiment was conducted to test UAV route planning effect,and a case with three scenarios was studied to analyze the impact of different road segment lengths on UAV route planning.The case results show that the optimized cruise distance and the number of UAVs used decrease by an average of 38.43% and 33.33%,respectively.Additionally,shortening or extending the length of road segments has different impacts on UAV route planning.
基金Project(51078086)supported by the National Natural Science Foundation of China
文摘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.
文摘According to the characteristics and requirements of urban vegetable logistics and distribution, the optimization model is established to achieve the minimum distribution cost of distribution center. The algorithm of artificial bee colony is improved, and the algorithm based on MATLAB software is designed to solve the model successfully. At the same time, combined with the actual case, the two algorithms are compared to verify the effectiveness of the improved artificial bee colony algorithm in the optimization of urban vegetable distribution path.
文摘AGRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation.One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon.Currently,the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise.The distribution of heavy winds andwaves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution,which significantly enhances the challenge of the captain’s preparation for avoiding typhoon navigation.It is now necessary to find a solution to the challenge of designing a highsafety and effective ship navigation path to avoid typhoons.The T_GRASP algorithm is suggested to optimize the candidate set’s structure based on the GRASP algorithm’s frame.The algorithm can guarantee the safety of the ship to avoid typhoons and assure high route efficiency by using the lowest risk function,the shortest sailing time,and the least fuel consumption as the objective functions and the ship speed and highest safety as the model constraints.The outcomes of the simulation demonstrate the superiority of the suggested T_GRASP algorithm over both the conventional A∗algorithm and the ant colony algorithm.In addition to addressing issues with the traditional A∗algorithm,like its wide search space and poor efficiency,the proposed algorithm also addresses issues with the ant colony algorithm,like its excessive iterations and sluggish convergence.
文摘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%.
文摘The future aeronautical network will be based on IPv6 and the services over the aeronautical network will be classified into 3 domains: Air Traffic Services (ATS), Airline Operational Services (AOS) and Passenger Information and Entertainment Services (PIES), among which the ATS and AOS domains are important for aircraft safety and airline business operation. Some schemes have been proposed to provide IP mobility support for aeronautical network, and Network Mobility (NEMO) scheme is the most promising one. However, using NEMO technology will lead to sub-optimal routing, so route optimization technology is highly desired for NEMO. A route optimization scheme is proposed for the ATS and AOS domains, which introduces the Correspondent Routers to realize the optimal routing and employs an improved procedure to reduce the handoff delay. The route optimization for the PIES domain is also discussed to provide better performance for some special scenarios.
基金supported by School Foundation of North University of ChinaPostdoctoral granted financial support from China Postdoctoral Science Foundation(20100481307)+1 种基金Natural Science Foundation of Shanxi(2009011018-3)National Natural Science Foundation of China(60876077)
文摘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.
文摘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.
文摘The present study aims to propose the method for the quantitative evaluation of safety concerning evacuation routes in case of earthquake disasters in urban areas using ACO （Ant Colony Optimization） algorithm and GIS （Geographic Information Systems）. Regarding the safety evaluation method, firstly, the similarity in safety was focused on while taking into consideration road blockage probability, and after classifying roads by means of the hierarchical cluster analysis, the congestion rates of evacuation routes using ACO simulations were estimated. Based on these results, the multiple evacuation routes extracted were visualized on digital maps by means of GIS, and its safety was evaluated. Furthermore, the selection of safe evacuation routes between evacuation sites, for cases when the possibility of large-scale evacuation after an earthquake disaster is high, is made possible. As the safety evaluation method is based on public information, by obtaining the same geographic information as the present study, it is effective in other areas regardless of whether the information is of the past and future. Therefore, in addition to spatial reproducibility, the safety evaluation method also has high temporal reproducibility. Because safety evaluations are conducted on evacuation routes based on quantified data, highly safe evacuation routes that are selected have been quantitatively evaluated, and thus serve as an effective indicator when selecting evacuation routes.
文摘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.
文摘In recent years, Japan, and especially rural areas have faced the growing problems of debt-ridden local railway lines along with the population decline and aging population. Therefore, it is best to consider the discontinuation of local railway lines and introduce replacement buses to secure the transportation methods of the local people especially in rural areas. Based on the above background, targeting local railway lines that may be discontinued in the near future, appropriate bus stops when provided with potential bus stops were selected, the present study proposed a method that introduces routes for railway replacement buses adopting ant colony optimization (ACO). The improved ACO was designed and developed based on the requirements set concerning the route length, number of turns, road width, accessibility of railway lines and zones without bus stops as well as the constraint conditions concerning the route length, number of turns and zones without bus stops. Original road network data were generated and processed adopting a geographic information systems (GIS), and these are used to search for the optimal route for railway replacement buses adopting the improved ACO concerning the 8 zones on the target railway line (JR Kakogawa line). By comparing the improved ACO with Dijkstra’s algorithm, its relevance was verified and areas needing further improvements were revealed.
文摘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.
