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Fluid-structure interaction in the context of shape optimization and computational wind engineering 1

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1st international workshop on Computational Engineering - Fluid-Structure Interactions, FSI 2009

作者： Hojjat, M. Stavropoulou, E. Gallinger, T. Israel, U. Wüchner, R. Bletzinger, K.-U. Lehrstuhl für Statik Technische Universität München München Germany

ISBN: (数字)9783642142062

ISBN: (纸本)9783642142055

Within this contribution, an integrated concept for the shape optimal design of light-weight and thin-walled structures like shells and membranes subject to fluid flow is presented. The Nested Analysis and Design approach is followed and a partitioned FSI simulation for the state analysis is embedded. The gained modularity allows for the adaption of the single ingredients to various technical applications by choosing appropriate coupling algorithms for the solution of the coupled problem and the sensitivity analysis as well as different strategies to describe the shapes to be optimized. A non-matching grid capability at the coupling interface supports this flexibility. The focus here is on problems of aeroelasticity in the field of Computational Wind Engineering. To ensure reliable results, investigations on the correct modeling as well as goal-oriented benchmarking are carried out. Moreover, special emphasis is given to the appropriate combination of different approaches for shape description in establishing the closed design cycle. Finally, the success of the overall solution and optimization strategy is demonstrated with an example of a hybrid, light-weight structure, subject to turbulent wind flow. © 2011 Springer.

关键词： Thin walled structures

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optimization of Parallel Manipulators Using Evolutionary algorithms 5th

Optimization of Parallel Manipulators Using Evolutionary Alg...

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5th international workshop on Soft Computing Models in Industrial applications , SOCO 2010

作者： Barbosa, Manuel R. Pires, E. J. Solteiro Lopes, António M. IDMEC–Pólo FEUP Faculdade de Engenharia da Universidade do Porto Rua Dr. Roberto Frias Porto4200–465 Portugal Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas Escola de Ciências e Tecnologia da Universidade de Trás-os-Montes e Alto Douro Quinta de Prados Vila Real5000–911 Portugal

ISBN: (纸本)9783642131608

Parallel manipulators have attracted the attention of researchers from different areas such as: high-precision robotics, machine-tools, simulators and haptic devices. The choice of a particular structural configuration and its dimensioning is a central issue to the performance of these manipulators. A solution to the dimensioning problem, normally involves the definition of performance criteria as part of an optimization process. In this paper the kinematic design of a 6-dof parallel robotic manipulator for maximum dexterity is analyzed. The condition number of the inverse kinematic jacobian is defined as the measure of dexterity and solutions that minimize this criterion are found through a genetic algorithm formulation. Subsequently a neuro-genetic formulation is developed and tested. It is shown that the neuro-genetic algorithm can find close to optimal solutions for maximum dexterity, significantly reducing the computational load. © Springer-Verlag Berlin Heidelberg 2010.

关键词： Inverse kinematics

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MLGA: A multilevel Cooperative Genetic Algorithm

MLGA: A Multilevel Cooperative Genetic Algorithm

引用

international Conference on Bio-Inspired Computing: Theories and applications, BICTA

作者： Reza Akbari Vahid Zeighami Koorush Ziarati Department of Computer Science and Engineering Shiraz University Shiraz Iran Department of Mathematics Shiraz University Shiraz Iran

This paper incorporate the multilevel selection (MLS) theory into the genetic algorithm. Based on this theory, a multilevel Cooperative Genetic Algorithm (MLGA) is presented. In MLGA, a species is subdivided in a set of populations, each population is subdivided in groups, and evolution occurs at two levels so called individual and group level. A fast population dynamics occurs at individual level. At this level, selection occurs between individuals of the same group. The popular genetic operators such as mutation and crossover are applied within groups. A slow population dynamics occurs at group level. At this level, selection occurs between groups of a population. A group level operator so called colonization is applied between groups in which a group is selected as extinct, and replaced by offspring of a colonist group. We used a set of well known numerical functions in order to evaluate performance of the proposed algorithm. The results showed that the MLGA is robust, and provides an efficient way for numerical function optimization.

关键词： Gallium optimization Heuristic algorithms Robustness

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Study on Water Pollution Diffusion by Artificial Immunity optimization Algorithm

Study on Water Pollution Diffusion by Artificial Immunity Op...

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international workshop on Intelligent Systems and applications, ISA

作者： Li Yu Jia-quan Wang School of Management Hefei University of Technology Hefei China Department of Computer Science and Technology Anhui University of Science and Technology Huainan China

ISBN: (纸本)9781424458721;9781424458745

Artificial immune algorithm is a new bionic algorithms, it becomes a hot spot. Artificial immune algorithm has self-adjustment ability and adaptive capacity of the environment and can deal with complex optimization problems in parallel. Immune algorithm takes concentration and affinity as standards. Thus low concentration, high-fit individuals have more breeding opportunities. As attention to the diversity of individuals of solution group, convergence of the algorithm is avoided. Select the test function to simulate diffusion experiment, the results showed that the immune algorithm is easy to achieve stable and good solution, it can accurately reflect the mix of major pollutants, the proliferation of laws. The algorithm provided a analysis tools for environmental capacity of water pollutants for the river basin to identify and volume control, and sustainable utilization of water resources.

关键词： Water pollution Immune system Rivers optimization methods Convergence Technology management Algorithm design and analysis Water resources Memory management Approximation algorithms

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Multi-criteria Manipulator Trajectory optimization Based on Evolutionary algorithms 5th

Multi-criteria Manipulator Trajectory Optimization Based on ...

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5th international workshop on Soft Computing Models in Industrial applications , SOCO 2010

作者： Pires, E. J. Solteiro Oliveira, P. B. de Moura Machado, J. A. Tenreiro Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas Escola de Ciências e Tecnologia da Universidade de Trás-os-Montes e Alto Douro Quinta de Prados Vila Real5000–801 Portugal Instituto Superior de Engenharia do Porto Instituto Politécnico do Porto Portugal

ISBN: (纸本)9783642131608

This paper proposes a method, based on a genetic algorithm, to generate smoth manipulator trajectories in a multi-objective perspective. The method uses terms proportional to the integral of the squared displacements in order to eliminate the jerk movement. In this work, the algorithm, based on NSGA-II and maximin sorting schemes, considers manipulators of two, three and four rotational axis (2R, 3R, 4R). The efficiency of the algorithm is evaluated, namely the extension of the front and the dispersion along the front. The effectiveness and capacity of the proposed approach are shown through simulations tests. © Springer-Verlag Berlin Heidelberg 2010.

关键词： Manipulators

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Arificial intelligence in machine tools design based on genetic algorithms application

Arificial intelligence in machine tools design based on gene...

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international workshop on Soft Computing applications (SOFA)

作者： G. Belgiu S. Nanu I. Silea Manufacturing Technology Department Politehnica University of Timişoara Timisoara Romania Department of Automation and Applied Informatics Politehnica University of Timişoara Timisoara Romania

The design of machine tools activity is an area with hundreds of years old. With the development of CAD/CAE systems, the engineers' work was greatly simplified. However, CAD/CAE systems are unable to overcome a critical threshold, thereby leaving the designer with many problems to be solved. Artificial intelligence field is also very exciting to develop this area. This paper presents a first attempt to introduce genetic algorithms in the design of machine tools.

关键词： Machine tools Manufacturing Artificial intelligence optimization Vibrations Kinematics Software

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Comparison of various encoding schemes for tree in Biobjective optimization scenario

Comparison of various encoding schemes for tree in Biobjecti...

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international workshop on Soft Computing applications (SOFA)

作者： Amit Kumar Singh Sanger Pramod Kumar Singh ABV Indian Institute of Information Technology and Management Gwalior India

To find MST (Minimum Spanning Trees) in complete graph is a classical problem in operation research having network design as an important application. It is possible to solve MST problem efficiently, but its Biobjective versions are NP hard. In this paper, we present a comparison of two encoding schemes for representing tree in Biobjective optimization scenario. The three different instances of Biobjective MST have been solved by using two different encoding methods in the evolutionary algorithms; Pareto optimal front obtained has been taken into account for comparative study. Our evolutionary computation approach involves Biobjective MST problem using NSGAII (Nondominated Sorting Genetic Algorithm II) approach. We compare edge sets encoding with Prüfer encoding in evolutionary algorithm for Biobjective MST, we find edge sets encoding outperforms the Prüfer in Biobjective optimization scenario.

关键词： Encoding Algorithm design and analysis optimization Evolutionary computation Sorting Pediatrics Memetics

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Digital Filter Design Using Evolutionary algorithms

Digital Filter Design Using Evolutionary Algorithms

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international workshop on Intelligent Systems and applications, ISA

作者： Huicong Wu Xuejun Song School of Information Science & Engineering Hebei University of Science and Technology Shijiazhuang China Institute of Electrostatic and electromagnetic protection Ordnance Engineering College Shijiazhuang China HATFL. College of Physics and Information Engineering Hebei Normal University Shijiazhuang China

ISBN: (纸本)9781424458721;9781424458745

Evolutionary approaches have been used in a large variety of design domains, from aircraft engineering to the designs of filters. An alternative approaches to the design of digital filter have been proposed using evolutionary algorithms and the concept of Evolvable Hardware. In this paper, clustering and Pareto optimization are combined into a single evolutionary design algorithm to prevent the system from converging prematurely to a local minimum and to encourage a number of different designs that fulfill the design criteria. This approach is demonstrated in the domain of digital filter design using a polar coordinate based pole-zero representation. The results demonstrate that the evolutionary process is able to create designs that are competitive with those created using a conventional design process. They also demonstrate that each evolutionary run can produce a number of different designs with similar fitness values, but very different characteristics.

关键词： Digital filters Algorithm design and analysis Evolutionary computation Aircraft propulsion Aerospace engineering Design engineering Hardware Pareto optimization Clustering algorithms Process design

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optimization of S-Boxes by Evolving

Optimization of S-Boxes by Evolving

引用

international workshop on Intelligent Systems and applications, ISA

作者： Zhongping Qin Qi Yang Li Zhai Sch. of Software Eng. Huazhong Univ. of Sci & Tech Wuhan China Sch. of Comput. Wuhan Univ. Wuhan China

The Substitution Box (S-Box for short) is the core component of a block cipher. The strength of a block cipher basically depends on the cryptography property of the S-Box it employs. Designers use "nonlinearity", "autocorrelation" and "difference" as the S-Box designing criteria. In this paper, we focus on optimizing S-Boxes by two heuristic methods - Genetic Algorithm and Simulated Annealing. Quite a lot of 8×8 S-Boxes with a joint feature value (Nonlinearity, Autocorrelation) = (102, 80) can be gotten just by our GA or SA with a steady probability. Both our methods are comparable to J. Clark's hybrid method (Simulated Annealing combined with Hill Climbing).

关键词： Boolean functions Cryptography Simulated annealing Autocorrelation Computational modeling Genetic algorithms Hamming weight Hamming distance Software engineering optimization methods

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An Improved Artificial Bee Colony Algorithm

An Improved Artificial Bee Colony Algorithm

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international workshop on Intelligent Systems and applications, ISA

作者： Fei Kang Junjie Li Haojin Li Zhenyue Ma Qing Xu Faculty of Infrastructure Engineering Dalian University of Technology Dalian China School of Hydraulic Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781424458721;9781424458745

Artificial bee colony (ABC) algorithm is one of the most recently proposed swarm intelligence algorithms for global optimization. It performs well in most cases; however, there still exist some problems it cannot solve very well. This paper presents a novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the Hooke Jeeves pattern search and the ABC. The main purpose is to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy. The proposed algorithm is tested on 7 benchmark functions including a wide range of dimensions. Numerical results show that the new algorithm is promising in terms of convergence speed, success rate and solution accuracy.

关键词： Particle swarm optimization Artificial intelligence Benchmark testing Convergence of numerical methods Performance analysis

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