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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yin-Zhang Guo Xiao-Fen Yan Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan Shanxi Province China

The problem of decoupling to time, space and flow in distributed object-oriented middleware asynchronous communication is studied in this paper. We adopt publish/subscribe (P/S) scheme in CORBA distributed circumstance based on analysis to the problem in current distributed object-oriented middleware communication mechanism and build CORBA communication system based on P/S model. At the same time, in order to solve the problem of decoupling to the three aspects in distributed object-orient middleware asynchronous communication we introduce mobile agent technique in P/S middleware broker system to establish an asynchronous communication algorithm based on mixture model of agent and P/S.

关键词： Asynchronous communication Middleware Object oriented modeling Mobile agents Mobile communication Space technology Computational modeling computer simulation computer applications application software

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Survey of stochastic diffusion search

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2008年第3期21卷 351-356页

作者： Wang, Li-Fang Zeng, Jian-Chao Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan 030024 China College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou 730050 China

As one of swarm intelligence optimization algorithms, the stochastic diffusion search is characterized by partial function evaluation and one-to-one recruitment mechanism. These characteristics make the algorithm high computation efficiency and robustness of the stochastic diffusion search. Based on the survey of basic principles and the research actuality of stochastic diffusion search, the existing problem and features are analyzed, and some future research directions about the stochastic diffusion search are delineated.

关键词： Surveys

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A novel exponential type swarming of foraging and obstacle-avoidance behaviour modelling and simulating research on collective motion in multi-obstacle environment

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3rd International Symposium on Intelligence Computation and applications, ISICA 2008

作者： Xue, Zhi Bin Zeng, Jian Chao College of Electric and Information Engineering Lanzhou University of Technology Lanzhou 730050 China Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan 030024 China Department of Chemical Machinery Chemical Engineering College Qinghai University Xining 810016 China

ISBN: (纸本)3540921362

A novel Lagrangian "individual-based" isotropic continuous time exponential type swarming model with a family of attraction/repulsion function is proposed in this article. The stability of aggregating behavior of the swarm systems is verified by computer numerical imitation. Numerical simulation results further indicate that the individual members living in group during the course of coordinative motion can realize the collision-eluding obstacles and ensure mutual aggregating behaviour, the motion of each individual member is a combination of the inter-individual interactions and the interaction of the member with external environment. Better self-adaptability of surrounding environment and practicability are embodied out in the proposed model. © 2008 Springer Berlin Heidelberg.

关键词： Continuous time systems

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Swarm robots search when local sense and interactions

Swarm robots search when local sense and interactions

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World Congress on Intelligent Control and Automation (WCICA)

作者： Songdong Xue Jianchao Zeng Division of System Simulation and Computer Application Taiyuan University of Technology Taiyuan China College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China

Swarm robots possess the potential to save lives by providing the rescuers location of victim during the most critical early hours. The ongoing project of swarm robots for search victim in coal mine disaster areas focuses on the modeling approach and control policies. This paper modeled such distributed system at an abstract level according to the swarm intelligence principles, i.e., limited sense capacity of individuals and local interaction mechanism, which used a virtual multiple agents search to localize target in a closed 2-D space. So, key definitions such as sensing function, neighborhood structure and initialization zone were given. The control over robots was attributed to two types: spiral control globally to search for signal cues and swarm intelligence-based control to search for target locally. Robots moving spirally to search cues can offer evidence for using swarm intelligence algorithm to search target. Taking characteristics of robots into account, we obtained the properties of the system by changing different parameters including communication range and sense scope in experiment. The simulation results indicate the validity of the control strategy proposed.

关键词： Robots Robot sensing systems Particle swarm optimization Computational modeling Electronic mail Olfactory Electric potential

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Cooperative particle swarm optimization for steel making scheduling

Cooperative particle swarm optimization for steel making sch...

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3rd International Conference on Natural Computation, ICNC 2007

作者： Huimin, Gao Jianchao, Zeng Division of System Simulation and Computer Application Taiyuan University of Science and Technology Shanxi 030024 China

ISBN: (纸本)0769528759

0-1 Integer programming model of steel making scheduling was presented. Boolean algebra was applied to restrict the search space of Particle Swarm Optimization to 0-1 space. As for the difficulty of constraint problem of 0-1 integer programming, a Cooperative Particle Swarm Optimization(CPSO) algorithm was proposed, which embody two particle swarms, one's goal is to minimize the objective function, the other is to meet the constraint condition. Two particle swarms cooperate to solve the 0-1 integer programming problem. The CPSO algorithm has been applied to solve the steel making scheduling problem successfully. © 2007 IEEE.

关键词： Global optimization

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Research of asynchronous communication messaging model based on time decoupling in distributed object-oriented middleware

Research of asynchronous communication messaging model based...

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SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing

作者： Yanhong, Zhao Yinzhang, Guo Shangwang, Bai Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan Shanxi Province China

ISBN: (纸本)0769529097

To solve the problem that the current distributed object-oriented middleware messaging communication mechanism doesn't support time decoupling and service quality control, a new asynchronous communication model TIAIM (Time Independent Asynchronous Invoke Model) which can support asynchronous messaging and time decoupling is presented, we adopted message conversion layer in client to pick up, package and convert the asynchronous message, and convert original request to a routed message, and we designed a software route agent to achieve asynchronous message transmission and retransmission. TIAIM model supports asynchronous messaging, time decoupling and service quality effectively. This paper also provides algorithm of message conversion layer and software route agent. © 2007 IEEE.

关键词： Message passing

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Self-adjusting predicted particle swarm optimization

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Journal of Information and Computational Science 2007年第2期4卷 483-496页

作者： Cui, Zhihua Zeng, Jianchao Sun, Guoji State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an 710049 China Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan 030024 China

Predicted particle swarm optimization is an enhanced version aiming to increase the utilization ratio of velocity information, and the performance heavily relies upon the parameters settings. According to control theory, the trajectories of position and velocity vectors of each particle can be both viewed as oscillatory links, and the relationship between inertia weight and accelerator coefficients is obtained. Thus, a self-adjusting parameter strategy is proposed. simulation results show the new proposed strategy is powerful and useful.

关键词： Numerical methods

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Hybrid heuristics scheduling algorithm for hot strip mill

Hybrid heuristics scheduling algorithm for hot strip mill

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3rd International Conference on Natural Computation, ICNC 2007

作者： Xiaoping, Wang Huimin, Gao Jianchao, Zeng School of Economics and Management Taiyuan University of Science and Technology Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)0769528759

This paper introduces the scheduling algorithm of a computer simulation and scheduling system for hot strip mill. The mathematical model of Hot Strip Mill Scheduling Problem (HSMSP) is formulated. A hybrid heuristics method is proposed, based on parallel strategy, which integrates domain expertise, Genetic Algorithm(GA) and Tabu Search(TS). Domain expertise is used to classify and sort production orders to generate initial solutions in parallel. GA is used to improve the initial solutions. And TS attempt to accelerate the convergence of the solutions by adopting swaps of 'single slab ' and 'slab section '. 'Single slab ' and 'slab section ', which we firstly introduced, are new adjacent solutions (neighborhood). simulation results have shown that the proposed method is feasible and efficient. © 2007 IEEE.

关键词： Heuristic algorithms

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Two-order particle swarm optimization model

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Jisuanji Yanjiu yu Fazhan/computer Research and Development 2007年第11期44卷 1825-1831页

作者： Hu, Jianxiu Zeng, Jianchao Division of System Simulation and Computer Application Taiyuan University of Science and Technology Taiyuan 030024 China

Particle swarm optimization (PSO) is an evolutionary computation technique developed by Kennedy and Eberhart in 1995. The underlying motivation for the development of PSO algorithm is social behavior of animals such as bird flocking, fish schooling, and swarm theory. Now PSO has been proved to be very effective for some problems. However, like other stochastic algorithms, PSO also suffers from the premature convergence problem, especially in the large scale and complex problems. In order to improve the global convergent ability of the standard particle swarm optimization (SPSO), a new version of particle swarm optimization named by a two-order PSO model is developed. Firstly, a two-order PSO model is introduced, its convergence analysis is given, and at the same time its parameter choices are studied. Secondly, a PSO model with the stochastic inertia weight is educed from the evolutionary equations of the two-order PSO. Thirdly, the two-order oscillating PSO with an oscillating factor is provided to adjust the influence of the acceleration on the velocity, which can guarantee the two-order PSO to converge to the global optimization validly. Finally, the above-proposed models are used to some benchmark optimizations. The experimental results show the proposed models can overcome the premature problem validly, and outperform the standard PSO in the global search ability and convergent speed.

关键词： Global optimization

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Self-learning particle swarm optimization based on environmental feedback

Self-learning particle swarm optimization based on environme...

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2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007

作者： Cai, Xingjuan Cui, Zhihua Zeng, Jianchao Tan, Ying Division of System Simulation and Computer Application Taiyuan University of Science and Technology Shanxi 030024 China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an 710049 China

ISBN: (纸本)0769528821

Particle swarm optimization (PSO) simulates the behaviors of birds ocking and £sh schooling. However, its biological background does not concern the environmental affection. Inspired by the interaction between environment and individuals, a new version - self-learning particle swarm optimization based on environmental feedback (SL-PSO), is proposed, in which two self-learning strategies are designed so that each particle adjusts its moving direction according to the feedback information from the environment. Furthermore, a mutation operator is introduced to avoid premature convergence phenomenon. simulation results show the proposed algorithm is effective and ef£cient. © 2007 IEEE.

关键词： Particle swarm optimization (PSO)

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