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Research on Data Routing Model Based on Ant Colony Algorithms 被引量:1
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作者 龚跃 吴航 +2 位作者 鲍杰 王君军 张艳秋 《Defence Technology(防务技术)》 SCIE EI CAS 2010年第4期269-272,共4页
Improved traditional ant colony algorithms,a data routing model used to the data remote exchange on WAN was presented.In the model,random heuristic factors were introduced to realize multi-path search.The updating mod... Improved traditional ant colony algorithms,a data routing model used to the data remote exchange on WAN was presented.In the model,random heuristic factors were introduced to realize multi-path search.The updating model of pheromone could adjust the pheromone concentration on the optimal path according to path load dynamically to make the system keep load balance.The simulation results show that the improved model has a higher performance on convergence and load balance. 展开更多
关键词 computer software data transmission ant colony algorithm routing model
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An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization
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作者 Zinah Khalid Jasim Jasim Sefer Kurnaz 《Computers, Materials & Continua》 SCIE EI 2024年第9期4643-4662,共20页
This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,shoul... This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness. 展开更多
关键词 STEGANOGRAPHY STEGANALYSIS capacity optimization ant colony algorithm
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Feature Extraction of Stored-grain Insects Based on Ant Colony Optimization and Support Vector Machine Algorithm 被引量:1
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作者 胡玉霞 张红涛 +1 位作者 罗康 张恒源 《Agricultural Science & Technology》 CAS 2012年第2期457-459,共3页
[Objective] The aim was to study the feature extraction of stored-grain insects based on ant colony optimization and support vector machine algorithm, and to explore the feasibility of the feature extraction of stored... [Objective] The aim was to study the feature extraction of stored-grain insects based on ant colony optimization and support vector machine algorithm, and to explore the feasibility of the feature extraction of stored-grain insects. [Method] Through the analysis of feature extraction in the image recognition of the stored-grain insects, the recognition accuracy of the cross-validation training model in support vector machine (SVM) algorithm was taken as an important factor of the evaluation principle of feature extraction of stored-grain insects. The ant colony optimization (ACO) algorithm was applied to the automatic feature extraction of stored-grain insects. [Result] The algorithm extracted the optimal feature subspace of seven features from the 17 morphological features, including area and perimeter. The ninety image samples of the stored-grain insects were automatically recognized by the optimized SVM classifier, and the recognition accuracy was over 95%. [Conclusion] The experiment shows that the application of ant colony optimization to the feature extraction of grain insects is practical and feasible. 展开更多
关键词 Stored-grain insects ant colony optimization algorithm Support vector machine Feature extraction RECOGNITION
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Disassembly sequence planning using component-joint graph and ant colony optimization
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作者 Zheng Menglei Tian Ling Liu Beibei 《Computer Aided Drafting,Design and Manufacturing》 2016年第1期54-57,共4页
Disassembly sequence planning is an important step of mechanical maintenance. This article presents an integrated study about the generation and optimizing algorithm of the disassembly sequence. Mechanical products ar... Disassembly sequence planning is an important step of mechanical maintenance. This article presents an integrated study about the generation and optimizing algorithm of the disassembly sequence. Mechanical products are divided into two categories of components and connectors. The article uses component-joint graph to represent assembly constraints, including the incidence constraints are represented by incidence matrix and the interference constraints are represented by interference constraints. The inspiring factor and pheromone matrix are calculated according to assembly constraints. Then the ant generates its own disassembly sequences one by one and updates the inspiring factor and pheromone matrix. After all iterations, the best disassembly sequence planning of components and connectors are given. Finally, an application instance of the disassembly sequence of the jack is presented to illustrate the validity of this method. 展开更多
关键词 disassembly sequence planning component-joint graph ant colony algorithms
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Algorithm for Low Altitude Penetration Aircraft Path Planning with Improved Ant Colony Algorithm 被引量:19
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作者 叶文 马登武 范洪达 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2005年第4期304-309,共6页
The ant colony algorithm is a new class of population basic algorithm. The path planning is realized by the use of ant colony algorithm when the plane executes the low altitude penetration, which provides a new method... The ant colony algorithm is a new class of population basic algorithm. The path planning is realized by the use of ant colony algorithm when the plane executes the low altitude penetration, which provides a new method for the path planning. In the paper the traditional ant colony algorithm is improved, and measures of keeping optimization, adaptively selecting and adaptively adjusting are applied, by which better path at higher convergence speed can be found. Finally the algorithm is implemented with computer simulation and preferable results are obtained. 展开更多
关键词 ant colony algorithm path planning keeping optimization adaptively adiusting low altitude penetration
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Weapon target assignment problem satisfying expected damage probabilities based on ant colony algorithm 被引量:26
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作者 Wang Yanxia Qian Longjun Guo Zhi Ma Lifeng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第5期939-944,共6页
A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed. In order to save armament resource and attack the targets effectively, the strategy of the we... A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed. In order to save armament resource and attack the targets effectively, the strategy of the weapon assignment is that the target with greater threat degree has higher priority to be intercepted. The effect of this WTA model is not maximizing the damage probability but satisfying the whole assignment result. Ant colony algorithm has been successfully used in many fields, especially in combination optimization. The ant colony algorithm for this WTA problem is described by analyzing path selection, pheromone update, and tabu table update. The effectiveness of the model and the algorithm is demonstrated with an example. 展开更多
关键词 weapon target assignment ant colony algorithm optimization.
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Ant colony optimization algorithm and its application to Neuro-Fuzzy controller design 被引量:11
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作者 Zhao Baojiang Li Shiyong 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第3期603-610,共8页
An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and s... An adaptive ant colony algorithm is proposed based on dynamically adjusting the strategy of updating trail information. The algorithm can keep good balance between accelerating convergence and averting precocity and stagnation. The results of function optimization show that the algorithm has good searching ability and high convergence speed. The algorithm is employed to design a neuro-fuzzy controller for real-time control of an inverted pendulum. In order to avoid the combinatorial explosion of fuzzy rules due tσ multivariable inputs, a state variable synthesis scheme is employed to reduce the number of fuzzy rules greatly. The simulation results show that the designed controller can control the inverted pendulum successfully. 展开更多
关键词 neuro-fuzzy controller ant colony algorithm function optimization genetic algorithm inverted pen-dulum system.
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An adaptive ant colony system algorithm for continuous-space optimization problems 被引量:20
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作者 李艳君 吴铁军 《Journal of Zhejiang University Science》 CSCD 2003年第1期40-46,共7页
Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is pr... Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates.Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved. 展开更多
关键词 ant colony algorithm Continuous space optimization Pheromone update strategy
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Optimization of Air Route Network Nodes to Avoid ″Three Areas″ Based on An Adaptive Ant Colony Algorithm 被引量:9
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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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Ant colony ATTA clustering algorithm of rock mass structural plane in groups 被引量:9
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作者 李夕兵 王泽伟 +1 位作者 彭康 刘志祥 《Journal of Central South University》 SCIE EI CAS 2014年第2期709-714,共6页
Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by ... Based on structural surface normal vector spherical distance and the pole stereographic projection Euclidean distance,two distance functions were established.The cluster analysis of structure surface was conducted by the use of ATTA clustering methods based on ant colony piles,and Silhouette index was introduced to evaluate the clustering effect.The clustering analysis of the measured data of Sanshandao Gold Mine shows that ant colony ATTA-based clustering method does better than K-mean clustering analysis.Meanwhile,clustering results of ATTA method based on pole Euclidean distance and ATTA method based on normal vector spherical distance have a great consistence.The clustering results are most close to the pole isopycnic graph.It can efficiently realize grouping of structural plane and determination of the dominant structural surface direction.It is made up for the defects of subjectivity and inaccuracy in icon measurement approach and has great engineering value. 展开更多
关键词 rock mass discontinuity cluster analysis ant colony ATTA algorithm distance function Silhouette index
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Improved Ant Colony-Genetic Algorithm for Information Transmission Path Optimization in Remanufacturing Service System 被引量:7
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作者 Lei Wang Xu-Hui Xia +2 位作者 Jian-Hua Cao Xiang Liu Jun-Wei Liu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2018年第6期106-117,共12页
The information transmission path optimization(ITPO) can often a ect the e ciency and accuracy of remanufactur?ing service. However, there is a greater degree of uncertainty and complexity in information transmission ... The information transmission path optimization(ITPO) can often a ect the e ciency and accuracy of remanufactur?ing service. However, there is a greater degree of uncertainty and complexity in information transmission of remanu?facturing service system, which leads to a critical need for designing planning models to deal with this added uncer?tainty and complexity. In this paper, a three?dimensional(3D) model of remanufacturing service information network for information transmission is developed, which combines the physic coordinate and the transmitted properties of all the devices in the remanufacturing service system. In order to solve the basic ITPO in the 3D model, an improved 3D ant colony algorithm(Improved AC) was put forward. Moreover, to further improve the operation e ciency of the algorithm, an improved ant colony?genetic algorithm(AC?GA) that combines the improved AC and genetic algorithm was developed. In addition, by taking the transmission of remanufacturing service demand information of certain roller as example, the e ectiveness of AC?GA algorithm was analyzed and compared with that of improved AC, and the results demonstrated that AC?GA algorithm was superior to AC algorithm in aspects of information transmission delay, information transmission cost, and rate of information loss. 展开更多
关键词 Remanufacturing service Information transmission Path optimization ant colony algorithm Genetic algorithm
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Blackboard Mechanism Based Ant Colony Theory for Dynamic Deployment of Mobile Sensor Networks 被引量:5
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作者 Guang-ping Qi Ping Song Ke-jie Li 《Journal of Bionic Engineering》 SCIE EI CSCD 2008年第3期197-203,共7页
A novel bionic swarm intelligence algorithm, called ant colony algorithm based on a blackboard mechanism, is proposed to solve the autonomy and dynamic deployment of mobiles sensor networks effectively. A blackboard m... A novel bionic swarm intelligence algorithm, called ant colony algorithm based on a blackboard mechanism, is proposed to solve the autonomy and dynamic deployment of mobiles sensor networks effectively. A blackboard mechanism is introduced into the system for making pheromone and completing the algorithm. Every node, which can be looked as an ant, makes one information zone in its memory for communicating with other nodes and leaves pheromone, which is created by ant itself in naalre. Then ant colony theory is used to find the optimization scheme for path planning and deployment of mobile Wireless Sensor Network (WSN). We test the algorithm in a dynamic and unconfigurable environment. The results indicate that the algorithm can reduce the power consumption by 13% averagely, enhance the efficiency of path planning and deployment of mobile WSN by 15% averagely. 展开更多
关键词 ant colony algorithm wireless sensor network blackboard mechanism bionic swarm intelligence algorithm
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Improved Multi-objective Ant Colony Optimization Algorithm and Its Application in Complex Reasoning 被引量:3
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作者 WANG Xinqing ZHAO Yang +2 位作者 WANG Dong ZHU Huijie ZHANG Qing 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2013年第5期1031-1040,共10页
The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become... The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system. 展开更多
关键词 fault reasoning ant colony algorithm Pareto set multi-objective optimization complex system
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Spatial quality evaluation for drinking water based on GIS and ant colony clustering algorithm 被引量:4
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作者 侯景伟 米文宝 李陇堂 《Journal of Central South University》 SCIE EI CAS 2014年第3期1051-1057,共7页
To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used.... To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN. 展开更多
关键词 geographical information system (GIS) ant colony clustering algorithm (ACCA) quality evaluation drinking water spatial analysis
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Research on UAV cloud control system based on ant colony algorithm 被引量:3
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作者 ZHANG Lanyong ZHANG Ruixuan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2022年第4期805-811,共7页
In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the ... In the cloud era, the control objects are becoming larger and the information processing is more complex, and it is difficult for traditional control systems to process massive data in a timely manner. In view of the difficulty of data processing in the cloud era, it is extremely important to perform massive data operations through cloud servers. Unmanned aeriel vehicle(UAV) control is the representative of the intelligent field. Based on the ant colony algorithm and incorporating the potential field method, an improved potential field ant colony algorithm is designed. To deal with the path planning problem of UAVs, the potential field ant colony algorithm shortens the optimal path distance by 6.7%, increases the algorithm running time by39.3%, and increases the maximum distance by 24.1% compared with the previous improvement. The cloud server is used to process the path problem of the UAV and feedback the calculation results in real time. Simulation experiments verify the effectiveness of the new algorithm in the cloud environment. 展开更多
关键词 ant colony algorithm potential field method cloud server path planning
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Optimizing Fresh Logistics Distribution Route Based on Improved Ant Colony Algorithm 被引量:3
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作者 Daqing Wu Ziwei Zhu +1 位作者 Dong Hu Romany Fouad Mansour 《Computers, Materials & Continua》 SCIE EI 2022年第10期2079-2095,共17页
With the rapid development of the fresh cold chain logistics distribution and the prevalence of low carbon concept,this paper proposed an optimization model of low carbon fresh cold chain logistics distribution route ... With the rapid development of the fresh cold chain logistics distribution and the prevalence of low carbon concept,this paper proposed an optimization model of low carbon fresh cold chain logistics distribution route considering customer satisfaction,and combined with time,space,weight,distribution rules and other constraints to optimize the distribution model.At the same time,transportation cost,penalty cost,overloading cost,carbon tax cost and customer satisfaction were considered as the components of the objective function,and the thought of cost efficiency was taken into account,so as to establish a distribution model based on the ratio of minimum total cost to maximum satisfaction as the objective function.Then,the improved A∗algorithm and ant colony algorithm were used to construct the model solution.Through the simulation analysis results of different calculation examples,the effectiveness,efficiency and correctness of the design of the single target low-carbon fresh agricultural products cold chain model by using the improved ant colony algorithm were verified. 展开更多
关键词 Carbon tax cost vehicle routing problem cold chain ant colony algorithm
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Ant Colony Algorithm for Solving QoS Routing Problem 被引量:3
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作者 SUNLi-iuan WANGLiang-jun WANGRu-chuan 《Wuhan University Journal of Natural Sciences》 EI CAS 2004年第4期449-453,共5页
Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least\|cost quality of service (QoS) unicast rou... Based on the state transition rule, the local updating rule and the global updating rule of ant colony algorithm, we propose an improved ant colony algorithm of the least\|cost quality of service (QoS) unicast routing. The algorithm is used for solving the routing problem with delay, delay jitter, bandwidth, and packet loss\|constrained. In the simulation, about 52.33% ants find the successful QoS routing , and converge to the best. It is proved that the algorithm is efficient and effective. 展开更多
关键词 ant colony algorithm QOS unicast routing
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Improved Ant Colony Algorithm for Vehicle Scheduling Problem in Airport Ground Service Support 被引量:3
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作者 Yaping Zhang Ye Chen +2 位作者 Yu Zhang Jian Mao Qian Luo 《Journal of Harbin Institute of Technology(New Series)》 CAS 2023年第1期1-12,共12页
Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for... Support vehicles are part of the main body of airport ground operations,and their scheduling efficiency directly impacts flight delays.A mathematical model is constructed and the responsiveness of support vehicles for current operational demands is proposed to study optimization algorithms for vehicle scheduling.The model is based on the constraint relationship of the initial operation time,time window,and gate position distribution,which gives an improvement to the ant colony algorithm(ACO).The impacts of the improved ACO as used for support vehicle optimization are compared and analyzed.The results show that the scheduling scheme of refueling trucks based on the improved ACO can reduce flight delays caused by refueling operations by 56.87%,indicating the improved ACO can improve support vehicle scheduling.Besides,the improved ACO can jump out of local optima,which can balance the working time of refueling trucks.This research optimizes the scheduling scheme of support vehicles under the existing conditions of airports,which has practical significance to fully utilize ground service resources,improve the efficiency of airport ground operations,and effectively reduce flight delays caused by ground service support. 展开更多
关键词 airport surface traffic ground service support vehicle scheduling topology model improved ant colony algorithm response value
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Optimization design of drilling string by screw coal miner based on ant colony algorithm 被引量:3
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作者 张强 毛君 丁飞 《Journal of Coal Science & Engineering(China)》 2008年第4期686-688,共3页
It took that the weight minimum and drive efficiency maximal were as double optimizing target,the optimization model had built the drilling string,and the optimization solution was used of the ant colony algorithm to ... It took that the weight minimum and drive efficiency maximal were as double optimizing target,the optimization model had built the drilling string,and the optimization solution was used of the ant colony algorithm to find in progress.Adopted a two-layer search of the continuous space ant colony algorithm with overlapping or variation global ant search operation strategy and conjugated gradient partial ant search operation strat- egy.The experiment indicates that the spiral drill weight reduces 16.77% and transports the efficiency enhance 7.05% through the optimization design,the ant colony algorithm application on the spiral drill optimized design has provided the basis for the system re- search screw coal mine machine. 展开更多
关键词 screw coal miner optimization design ant colony algorithm two-layer search
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Multi-group ant colony algorithm based on simulated annealing method 被引量:2
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作者 朱经纬 芮挺 +1 位作者 廖明 张金林 《Journal of Shanghai University(English Edition)》 CAS 2010年第6期464-468,共5页
To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulat... To overcome the default of single search tendency, the ants in the colony are divided into several sub-groups. The ants in different subgroups have different trail information and expectation coefficients. The simulated annealing method is introduced to the algorithm. Through setting the temperature changing with the iterations, after each turn of tours, the solution set obtained by the ants is taken as the candidate set. The update set is obtained by adding the solutions in the candidate set to the previous update set with the probability determined by the temperature. The solutions in the candidate set are used to update the trail information. In each turn of updating, the current best solution is also used to enhance the trail information on the current best route. The trail information is reset when the algorithm is in stagnation state. The computer experiments demonstrate that the proposed algorithm has higher stability and convergence speed. 展开更多
关键词 ant colony algorithm simulated annealing method MULTI-GROUP candidate set update set
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