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New Differential Evolution Algorithm with a Second Enhanced Mutation Operator

New Differential Evolution Algorithm with a Second Enhanced ...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Changshou Deng Bingyan Zhao Anyuan Deng Rixin Hu School of Information Science and Technology Jiujiang University China

To improve the efficiency of the original differential evolution algorithm, a new differential evolution algorithm was proposed. A new framework with a single population was used to improve its' exploration ability. And a second enhanced mutation operator was used to ensure the exploitation of previous knowledge about the fitness landscape. Numerical experiments with typical benchmark functions show the proposed new version of differential evolution performs better than original differential evolution algorithm. Performances compared with dynamic differential evolution and particle swarm optimization algorithm show its superiority.

关键词： Genetic mutations Signal processing algorithms Convergence Particle swarm optimization Machine intelligence Fuzzy logic Information science Algorithm design and analysis Power engineering computing Competitive intelligence

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A Scalability Test for Accelerated DE Using Generalized Opposition-Based Learning

A Scalability Test for Accelerated DE Using Generalized Oppo...

引用

international Conference on Intelligent Systems Design and applications (ISDA)

作者： Hui Wang Zhijian Wu Shahryar Rahnamayan Lishan Kang State Key Laboratory of Software Engineering Wuhan University of China Wuhan China Faculty of Engineering and Applied Science Institute of Technology University of Ontario Oshawa ONT Canada

In this paper a scalability test over eleven scalable benchmark functions, provided by the current workshop (Evolutionary algorithms and other Metaheuristics for Continuous optimization Problems-A Scalability Test), are conducted for accelerated DE using generalized opposition-based learning (GODE). The average error of the best individual in the population has been reported for dimensions 50, 100, 200, and 500 in order to compare with the results of other algorithms which are participating in this workshop. Current work is based on opposition-based differential evolution (ODE) and our previous work, accelerated PSO by generalized OBL.

关键词： Scalability Life estimation System testing Acceleration Benchmark testing Evolutionary computation Robustness Chromium Intelligent systems Design optimization

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An Autogenerating Test Paper Method Based on Latent Semantic Analysis and Genetic Algorithm

An Autogenerating Test Paper Method Based on Latent Semantic...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Huming Gao Yanjie Li Inf. Manage. Dept Tianjin Univ. of Econ. & Finance Tianjin

It is a multi-objective optimization problem to autogenerate a test paper from test bank. In this paper an autogenerating test paper method based on latent semantic analysis and genetic algorithm is proposed. Firstly the relationships of keywords among test items in a test bank are analyzed with LSA, and the weights of the test items are calculated. Then using the Genetic Algorithm to compose the test paper accorded to the weights. The proposed method can effectively select test items from Chinese test bank to compose a test paper.

关键词： Testing Algorithm design and analysis Genetic algorithms optimization methods Matrix decomposition Information management Finance Singular value decomposition Information analysis Education

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Interactive system design and end-to-end optimization in sensor networks

Interactive system design and end-to-end optimization in sen...

引用

作者： Grythe, Knut Lie, Arne Balasingham, Ilangko SINTEF ICT Dept. of Communication Systems Norway Rikshospitalet University Hospital Dept. of Electronics and Telecommunications Norwegian University of Science and Technology Norway

ISBN: (纸本)9781424452538

This paper proposes an application oriented four layered quality of service (QoS) stack for wireless sensor networks (WSN), including a supporting system architecture for interacting with WSNs using the MPEG-21 multimedia framework in an medical application setting. The application of the WSNs is signal processing algorithms reporting elaborated observed sensor data to external users. The QoS model supports the tradeoff between end-users expected QoS combined with optimized energy consumption. The MPEG-21 standard is chosen as the media resource framework due to the fact that future hospitals will have networks comprising WSNs supporting an always increasing amount of both low rate medical sensor data as well as high rate audiovisual content. Furthermore due to the heterogeneous set of user terminals and network resources, media adaptation will become important to provide reliable and robust quality of service. In this paper, we argue for an extension of the MPEG-21 terminology for use in biomedical wireless sensor networks and incorporate the requirements needed for medical applications. © 2009 IEEE.

关键词： Quality of service

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Research on a Scale-Free Network with Tunable Clustering Coefficient

Research on a Scale-Free Network with Tunable Clustering Coe...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Qin Yang Lulong Lan Jianhui Zhang National Digital Switching System Engineering Technological Research and Development Center Zhengzhou Henan China

Network topology plays an important role in design and optimization of routing protocols and network algorithms. Based on the characteristics of real networks and local world phenomenon, this paper proposes a evolving scale-free network with tunable clustering coefficient(SFTC) by introducing triad formation, which dynamically simulates the adding and deleting of nodes or edges, and the evolvements inside or outside the local world. The evaluation of C++ and Matlab not only support the analytical calculation of model's degree distribution, but also indicates that the clustering coefficient can be tuned to be a preferable value and the SFTC model totally reproduces the properties of real network.

关键词： Mathematical model Network topology IP networks Algorithm design and analysis Design optimization Routing protocols Switching systems Design engineering Systems engineering and theory Research and development

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Three Sub-Swarm Particle Swarm optimization Algorithm

Three Sub-Swarm Particle Swarm Optimization Algorithm

引用

international workshop on Intelligent Systems and applications, ISA

作者： Ming-Ming Bai Hui Sun Lie-Yang Wu Ze-Tao Jiang Wen-Huan Wu Dept. of Comput. Sci. & Technol. NanChang Inst. of Technol. Nanchang Nanchang Hangkong University Nanchang Hangkong University Nanchang Jiangxi CN

In order to overcome the drawback of the standard PSO, such as being subject to falling into local optimization, an improved PSO algorithm based on three sub-swarms exchange is proposed. Firstly the method divides the whole swarm into three sub-swarms which evolve jointly according to three different models, that is, one evolves with the standard PSO model, and the second with social only model and the third with cognition only model respectively. When the community evolution achieves the equilibrium state, we exchange some particles between the three different sub-swarms, which can increase the information exchange between the sub-swarms, improve the population diversity and reduce the possibility of getting local extreme value. The results of simulation show that the proposed algorithm in the paper has the better optimization performance than the standard PSO.

关键词： Particle swarm optimization Convergence Iterative algorithms Acceleration Sun Computer science Cognition Cultural differences Birds Testing

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A Hybrid Particle Swarm optimization Algorithm for Multimodal Function optimization

A Hybrid Particle Swarm Optimization Algorithm for Multimoda...

引用

international workshop on Intelligent Systems and applications, ISA

作者： Jirong Gu Lin Lin Hui Wang College of Geography and Resources Sciences Sichuan Normal University China Department of Computer Science Yili Normal School Yining China State Key Laboratory of Software Engineering Wuhan University of China China

Particle swarm optimization (PSO) has shown its good performance on numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid decline in velocity. In this paper, a hybrid PSO algorithm, called HPSO, is proposed, which employs a modified velocity model to guarantee a non-zero velocity. In addition, a Cauchy mutation operator conducted on the global best particle is used for improving the global search ability of PSO. Experimental studies on a suite of multimodal functions with many local minima show that the HPSO outperforms the standard PSO, CEP, Gaussian swarm with Gaussian mutation (GPSO+GJ) and Gaussian swarm with Cauchy mutation (GPSO+CJ) on most test functions.

关键词： Particle swarm optimization Genetic mutations Evolutionary computation Equations Software algorithms Educational institutions Geography Computer science Software engineering Convergence

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A Memetic Differential Evolution Algorithm for Continuous optimization

A Memetic Differential Evolution Algorithm for Continuous Op...

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international Conference on Intelligent Systems Design and applications (ISDA)

作者： Santiago Muelas Antonio La Torre José-María Peña CeSViMa Parque Tecnológico UPM Campus de Montegancedo Facultad de Informática Universidad Politécnica de Madrid Boadilla del Monte Madrid Spain CeSViMa Pozuelo de Alarcon Spain

Continuous optimization is one of the most active research lines in evolutionary and metaheuristic algorithms. Since CEC 2005 and CEC 2008 competitions, many different algorithms have been proposed to solve continuous problems. Despite there exist very good algorithms reporting high quality results for a given dimension, the scalability of the search methods is still an open issue. Finding an algorithm with competitive results in the range of 50 to 500 dimensions is a difficult achievement. This contribution explores the use of a hybrid memetic algorithm based on the differential evolution algorithm, named MDE-DC. The proposed algorithm combines the explorative/exploitative strength of two heuristic search methods, that separately obtain very competitive results in either low or high dimensional problems. This paper uses the benchmark problems and conditions required for the workshop on ¿evolutionary algorithms and other metaheuristics for "Continuous optimization Problems - A Scalability Test¿ chaired by Francisco Herrera and Manuel Lozano.

关键词： Evolution (biology) Search methods Large-scale systems Design optimization Scalability Evolutionary computation optimization methods Intelligent systems Benchmark testing Biology

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PARMETAOPT — Parallel metaheuristics framework for combinatorial optimization problems

PARMETAOPT — Parallel metaheuristics framework for combinat...

引用

IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Plamenka Borovska Ognian Nakov Milena Lazarova Department of Computer Systems Technical University of Sofia Sofia Bulgaria

The paper presents an experimental parallel metaheuristics framework for solving combinatorial optimization of grand challenge scientific and engineering problems that has been developed based on biologically inspired metaheuristics, modeling of social behavior and cultural evolution as well as trajectory-based methods. A prototype class library for metaheuristics is developed and several parallel computational models of metaheuristics for solving combinatorial optimization problems are implemented. The library contains implementations in C++ of parallel computational models for both population based and trajectory based metaheuristics. Some improvements in the parallel models are suggested and implemented in the library PARMETAOPT. The influence of the parameters on the performance of some of the parallel algorithms is analyzed using the developed parallel metaheuristics framework and performance tuning rules are suggested. The implementations are based on message passing with MPICH2 for the flat programming models and OpenMP API is used for multithreading in the hybrid programming models.

关键词： Biological system modeling Libraries Biology computing Concurrent computing Computational modeling optimization methods Design engineering Cultural differences Evolution (biology) Prototypes

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Multi-Agent in Ant Colony Algorithm Approach for Solving Traveling Salesman Problem

Multi-Agent in Ant Colony Algorithm Approach for Solving Tra...

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international workshop on Intelligent Systems and applications, ISA

作者： Dong-Sheng Xu Shi-Liang Yan Department of Information Technology Yulin University Yulin China Engineering & Technology Center Southwest University of Science and Technology Mianyang China

Traveling salesman problem (TSP) is a very hard and classical optimization problem in the field of operations research, and often-used benchmark for new optimization techniques. This paper will to bring up multi-agent approach for solving the TSP based on data mining algorithm, for the extraction of knowledge from a large set of TSP. The proposed approach supports the distributed solving to the TSP. It divides into three-tier, the first tier is ant colony optimization agent; the second-tier is genetic algorithm agent; and the third tier is fast local searching agent. In using an ant colony algorithm (ACA) for the TSP, an attribute-oriented induction methodology was used to explore the relationship between an operations' sequence and its attributes and a set of rules has been developed. These rules can duplicate the ACA's performance on identical problems. Ultimately, the experimental results have shown that the proposed hybrid approach has good performance with respect to the quality of solution and the speed of computation.

关键词： Traveling salesman problems Data mining Ant colony optimization Genetic algorithms Cities and towns Neural networks Information technology Operations research Data engineering Benchmark testing

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