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检索条件"主题词=Ant Colony Optimization algorithm"

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An Educational Tool for the ant colony optimization algorithm

An Educational Tool for the Ant Colony Optimization Algorith...

引用

1st International Workshop on Education Technology and Computer Science

作者： Li, Jing Liu, Wei Nanjing Agr Univ Sch Engn Nanjing Peoples R China

ISBN: (纸本)9780769535579

Researches in the ant colony optimization algorithm has been expanding rapidly both in academia and industry. The correlated courses have been offered at many universities. However, the teaching methods for the algorithm are not sufficient. This paper proposes an experimental tool for the teaching of the ant colony optimization algorithm. The traveling salesman problem is conducted as the application of the tool. In this context, the tool is developed with friendly graphical user interfaces for teaching the algorithms. Graduate students at Nanjing Agricultural University can use this tool to learn the ant colony algorithm. Experiments for the optimal design can be conducted by students through the manipulation of the parameters.

关键词： ant colony optimization algorithm Traveling salesman problem Teaching software Learning tool

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Adaptive Contract Net Protocol Based on ant colony optimization algorithm

Adaptive Contract Net Protocol Based on Ant Colony Optimizat...

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International Conference on Mechanics and Manufacturing Systems (ICMMS 2011)

作者： Tang Xian-lun Fan Zheng Li Ya-nan Cai Lin-qin Chongqing Univ Posts & Telecommun Minist Educ Key Lab Network Control & Intelligent Instrument Chongqing Peoples R China

ISBN: (纸本)9783037852750

An adaptive contract net protocol which can adapt to dynamic environment is proposed based on ant colony optimization algorithm. hi the negotiation process of task allocation, the probability of the contractor being selected is related with the contractor's credibility and ability. Several experiments are performed to show the advantages of this algorithm, it has a better decision quality when task recurrence rate (TRR) unchanged, and the communication traffic (CT) remains at a low level as TRR increases when the number of tasks (NT) unchanged. As a result, the algorithm can enhance the decision quality and reduce the communication traffic.

关键词： contract net protocol ant colony optimization algorithm task allocation

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Solutions to VRP in Home Delivery Based on ant colony optimization algorithm

Solutions to VRP in Home Delivery Based on Ant Colony Optimi...

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International Conference on Micro Nano Devices, Structure and Computing Systems

作者： Hu Meng-Jie Wang Jian-Ping Li Xiao-Min Henan Inst Sci & Technol Sch Econ & Management Luoyang Peoples R China Henan Inst Sci &Technol Sch Informat Engineer Luoyang Peoples R China Henan Inst Sci & Technol Sch Mech &Elect Luoyang Peoples R China

ISBN: (纸本)9783037850091

Home delivery is a new trend in logistics at present. The distribution path planning has a great impact on customer's satisfaction and the total cost of operation in home delivery industry. In This paper, we construct the distribution path planning problems in the industry of logistics and home delivery based on ant colony optimization algorithm, the optimal vehicle's number and the best distribution path can be found in the shortest time by using the model advised in the paper. It is found that there is no obvious correlation between the service and the total costs of delivery after the analysis. So, home delivery companies can select the optimal path planning, i.e. a lower cost of delivery and higher level of service, according to their service policies.

关键词： ant colony optimization algorithm Industry of Logistics and Home Delivery Path Planning VRP

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Dam deformation monitoring model based on neural network with ant colony optimization algorithm

Dam deformation monitoring model based on neural network wit...

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4th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2012)

作者： Wei Bo-wen Xu Zhen-kai Liu He-zhi Nanchang Univ Coll Civil Engn & Architecture Nanchang 330031 Peoples R China Coll Water Conservancy & Hydropower Hohai Univ Nanjing Peoples R China

ISBN: (纸本)9783037852842

Back propagation algorithm (BP) is widely used as a multilayer feedforward neural network model in the analysis of water engineering projects monitoring data, but it has low solution accuracy, slow search speed and easy to get into a local minimum. To overcome these shortcomings, in this paper, a new learning method of neural network with ant colony optimization (ACO) is introduced to achieve optimization solution of the model weights, the ACO-BP monitoring model of dam deformation is established as well. And actual examples show that the ant colony algorithm is effective and rapid.

关键词： ant colony optimization algorithm neural network deformation monitoring

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Improved ant colony optimization algorithm and Its Application for Path Planning of Mobile Robot in 3-D Space

Improved Ant Colony optimization Algorithm and Its Applicati...

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2nd IEEE International Conference on Advanced Computer Control

作者： Zhao Juan-ping Gao Xian-wen Liu Jin-gang Fu Xiu-hui Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9781424458479

An improved ant colony algorithm, differential evolution chaos ant colony optimization (DEACO) algorithm, was proposed to plan an optimal collision-free path for mobile robot in 3-D environment. It utilized differential evolution algorithm to update pheromone and chaos disturbance factor was added when pheromone updates for possible stagnation phenomenon. So it enhances escaping capability of algorithm, avoids path-deadlock situations as well as improves the efficiency of planning optimal path. The simulation results indicated that the optimal path on which the robot moves can reach safely and can be rapidly obtained under 3-D space environment, the effect being very satisfactory.

关键词： mobile robot path planning ant colony optimization algorithm differential evolution Chaos sinulation

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Application of ant colony optimization algorithm to Selection of Clusters Partners for Creative Industry

Application of Ant Colony Optimization Algorithm to Selectio...

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16th International Conference on Management Science and Engineering

作者： Li Yu-hua Harbin Univ Sci Technol Coll Management Harbin 150040 Peoples R China

ISBN: (纸本)9781424439706

Creative industry clusters are attracting particular interest as a result of the greater economic growth potential. The successful and effective creative industry clusters involve many factors,. of which selection of clusters Partners is a critical issue. In general, the purpose of partner selection for creative industry clusters is to enhance the economical efficiency as much as possible while simultaneously quickly responding to and satisfying practical requirements. So this paper applies ant colony optimization algorithm to select clusters partners for creative industry based on the establishment of the multi-goal decision-making model using 0-1 integer programming. In addition, the paper presents an example to illustrate the validity of the proposed algorithm to select clusters partners for creative industry.

关键词： ant colony optimization algorithm selection of clusters partners dynamic decision-making creative industry

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Wireless Networked Control Systems with neural networks and ant colony optimization algorithm 37

Wireless Networked Control Systems with neural networks and ...

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37th Chinese Control Conference (CCC)

作者： Xu, Qiang Yang, Jia Chongqing Technol & Business Univ Coll Comp Sci & Informat Engn Chongqing 400067 Peoples R China Chongqing Univ Technol Sch Elect & Elect Engn Chongqing 400054 Peoples R China

ISBN: (纸本)9789881563958

Due to Wireless network delay and large delay time of the controlled plant, the performance of the wireless networked control systems (WNCS) is deteriorates. In order to effectively eliminate the influence of network delay and large delay time, a novel structure of the WNCS is proposed that new Smith predictor combined with neural network prediction and identification model. Nonlinear system's delay time must be well identified. The abrupt mutation result from the training error sum square of the real output and the expected output of the neural network was used to identify the delay time. The input sample period of the neural network was changed so that it could discriminate the delay time of the nonlinear model. The discriminated large time-delay was applied to neural network prediction model. The errors between input and prediction model output were used to search PID controller parameters based on ant colony optimization algorithm. The method was applied to control boiler combustion system. The simulation results show that this scheme has much better advantage of celerity and robustness. This is the paper style requirement for the Chinese Control Conference. The writers of papers should and must provide normalized electronic documents in order for readers to search and read papers conveniently.

关键词： Large delay time Neural network prediction model ant colony optimization algorithm Wireless networked control systems (WNCS) Network delay Smith predictor

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Application of Real ant colony optimization algorithm to Solve Space Fractional Heat Conduction Inverse Problem 2nd

Application of Real Ant Colony Optimization Algorithm to Sol...

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22nd International Conference on Information and Software Technologies (ICIST)

作者： Brociek, Rafal Slota, Damian Silesian Tech Univ Inst Math Kaszubska 23 PL-44100 Gliwice Poland

ISBN: (纸本)9783319462547;9783319462530

In this paper inverse problem for the space fractional heat conduction equation is investigated. In order to reconstruct the heat transfer coefficient, functional defining error of approximate solution is created. To minimize this functional the Real ant colony optimization algorithm is used. The paper presents examples to illustrate the accuracy and stability of the presented algorithm.

关键词： Intelligent algorithm Inverse problem ant colony optimization algorithm Space fractional heat conduction equation

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Identification and Control based on Neural Networks and ant colony optimization algorithm

Identification and Control based on Neural Networks and Ant ...

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International Conference on Logistics Systems and Intelligent Management

作者： Xu, Qiang Lin, Jihai Yang, Jia Chongqing Technol & Business Univ Coll Comp Sci & Informat Engn Chongqing 400067 Peoples R China Chongqing Univ Technol Coll Elect & Informat Automat Masuho Yamanashi 4000502 Japan

ISBN: (纸本)9781424473281

It is difficult to have good performance to control large delay time system. A neural network identification method for nonlinear system's delay time was discussed. Using the abrupt mutation resulted from the training error sum square of the real output and the expected output of the network, this method changed the input sample period of the neural network so that it could discriminate the delay time of the nonlinear model. Combining the discrimination of neural network system with long time delay and the control method based on model prediction, searching PID controller parameters based on ant colony optimization algorithm, it was applied to control boiler combustion system. The simulation results show that this scheme has much better advantage of celerity and robustness.

关键词： Large Delay Time System Identification of Delay Time Prediction Model ant colony optimization algorithm

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A Hybrid ant colony optimization algorithm for Solving the Ring Arc-Loading Problem

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6th Hellenic Conference on Artificial Intelligence

作者： Bernardino, Anabela Moreira Bernardino, Eugenia Moreira Sanchez-Perez, Juan Manuel Gomez-Pulido, Juan antonio Vega-Rodriguez, Miguel Angel Polytech Inst Leiria Res Ctr Informat & Commun Sch Technol & Management Dept Comp Sci P-2411 Leiria Portugal Univ Extremadura Sch Polytech Dept Technol Comp & Commun Caceres 10071 Spain

ISBN: (纸本)9783642128417

The past two decades have witnessed tremendous research activities in optimization methods for communication networks. One important problem in communication networks is the Weighted Ring Arc-Loading Problem (combinatorial optimization NP-complete problem). This problem arises in engineering and planning of the Resilient Packet Ring (RPR) systems. Specifically, for a given set of non-split and uni-directional point-to-point demands (weights), the objective is to find the routing for each demand (i.e., assignment of the demand to either clockwise or counter-clockwise ring) so that the maximum arc load is minimised. In this paper, we propose a Hybrid ant colony optimization algorithm to solve this problem. We compare our results with the results obtained by the standard Genetic algorithm and Particle Swarm optimization, used in literature.

关键词： Communication Networks optimization algorithms ant colony optimization algorithm Weighted Ring Arc-Loading Problem

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