IUTAM Symposium on Evolutionary Methods in Mechanics : proceedings of the IUTAM Symposium held in Cracow, Poland, 24-27 September, 2002

Bibliographic Information

IUTAM Symposium on Evolutionary Methods in Mechanics : proceedings of the IUTAM Symposium held in Cracow, Poland, 24-27 September, 2002

edited by Tadeusz Burczyński and Andrzej Osyczka

(Solid mechanics and its applications, v. 117)

Kluwer Academic Publishers, c2004

  • : HB
  • : e-book

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Includes bibliographical references

Description and Table of Contents

Volume

: HB ISBN 9781402022661

Description

The IUTAM Symposium on Evolutionary Methods in Mechanics was held in Cracow, Poland, September 24-27, 2002. The site of the S- posium was Cracow University of Technology. The Symposium was - tended by 50 persons from 18 countries. In addition, several Polish students, Ph. D. students and research associates participated in the meeting. The Symposium provided an excellent opportunity for scholars of - chanics, computer sciences and arti?cial intelligence to interact and - change their points of view on the advanced computational and appli- tion aspects of the evolutionary methods in analysis and design of - chanical systems. Recently evolutionary methods have become the most e?ective tools for solving speci?c kinds of problems in mechanics, es- cially in structural and multidisciplinary optimization. The meeting was devotedtoboththeoreticalandpracticaldevelopmentsofcomputational mechanics methods drawing their inspiration from nature with part- ular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classi?er systems, evolutionary p- gramming and other evolutionary computation techniques in mechanics. The objective of the Symposium was to provide an international forum forfacilitatingtheexchangeofinformationamongresearchersinvolvedin computational intelligence methods based on evolutionary nature. The Symposium put special emphasis on evolutionary optimization in va- ous?eldsof mechanics. Thesubject of evolutionary optimization has- cently experienced a remarkable growth. New concepts, approaches and applicationsarebeing continually developed and exploited to provide- ?cient tools for solving a variety of optimization problems in mechanics.

Table of Contents

  • Preface. Committee and Sponsors. Evolutionary computation in crack problems
  • W. Beluch. Investigation of evolutionary algorithm effectiveness in optimal synthesis of certain mechanisms
  • K. Bialas-Hetltowski, et al. Minimum heat losses subjected to stiffness constraints: window frame optimization
  • R.A. Bialecki, M. Krol. Evolutionary computation in inverse problems
  • T. Burczynski, et al. Hang-glider wing design by genetic optimization
  • S. D'Angelo, et al. An error function for optimum dimension synthesis of mechanisms using genetic algorithms
  • I.F. de Bustos, et al. Evolutionary computation in thermoelastic problems
  • A. Dlugosz. Management of evolutionary MAS for multiobjective optimisation
  • G. Dobrowalski, M. Kisiel-Dorohinicki. PAMUC: a new method to handle with constraints and multiobjectivity in evolutionary algorithms
  • R. Filomeno Coelho, et al. A comparative analysis of 'controlled elitism' in the NGSA-II applied to frame optimization
  • D. Greiner, et al. IS-PAES: multiobjective optimization with efficient constraint handling
  • A. Hernandez Aguirre, et al. Optimization of aligned fiber laminate composites
  • Z. Hu, et al. Genetic algorithm for damage assessment
  • V.T. Johnson, et al. Estimation of parameters for a hydrodynamic transmission system mathematical model with the application of genetic algorithm
  • A. Kesy, et al. Study of safety of high-rise buildings using evolutionary search
  • S. Khajhpour, D.E. Grierson. Structural design using genetic algorithm
  • E. Kita, et al. The topology optimization using evolutionary search
  • G. Kokot, P. Orantek. Identification of CMM parametric errors by hierarchical genetic strategy
  • J. Kolodziej, et al. Genetic algorithm for fatigue crack detection in Timoshenko beam
  • M. Krawczuk, et al. Multicriteria designoptimization of robot gripper mechanisms
  • S. Krenich. Optimal design of multiple clutch brakes using a multistage evolutionary method
  • S. Krenich, A. Osyczka. Distributed evolutionary algorithms in optimization of nonlinear solids
  • W. Kus, T. Burczynski. Adaptive penalty strategies in genetic search for problems with inequality and equality constraints
  • C.-Y. Lin, W.-H. Wu. On the identification of linear elastic mechanical behaviour of orthopedic materials using evolutionary algorithms
  • M. Magalhaes Dourado, et al. Ranking pareto optimal solutions in genetic algorithm by using undifferentiation interval method
  • J. Montusiewicz. The effectiveness of probabilistic algorithms in shape and topology discrete optimisation of 2-D composite structures
  • A. Muc. Genetic algorithms in optimisation of resin hardening technological processes
  • A. Muc, P. Saj. Hybrid evolutionary algorithms in optimization of structures under dynamical loads
  • P. Orantek. Evolutionary optimization system (EOS) for design automation
  • O. Osyczka, et al. Evolutionary method for a universal motor geometry optimization
  • G. Papa, B. Korousic-Seljak. A review of the development and application of cluster oriented genetic algorithms
  • I.C. Parmee. Genetic algorithm optimization of hole shapes in a perforated elastic plate over a range of loads
  • S. Vigdergauz. An object oriented library for evolutionary programs with applications in partitioning of finite element meshes
  • J. Zola, et al.
Volume

: e-book ISBN 9781402022678

Description

This book contains papers presented at the IUTAM Symposium on Evolutionary Methods in Mechanics held in Cracow, Poland, September 24-27, 2002. Recently, Evolutionary algorithms and methods have become the most effective tools for solving specific kinds of problems in mechanics, especially in structural and multidisciplinary optimization. The book is devoted to both theoretical and practical developments of computational mechanics methods drawing their inspiration from nature with particular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming and other evolutionary computation techniques in mechanics. The Special emphasis is put on evolutionary optimization in various fields of mechanics. The subject of evolutionary optimization has recently experienced a remarkable growth. New concepts, approaches and applications are being continually and exploited to provide efficient tools for solving a variety of optimization problems in mechanics. Several important topics are presented: evolutionary methods in shape and topology optimization, evolutionary methods in size and material optimization, evolutionary methods in multiobjective optimization, in inverse problems of engineering mechanics, in biomechanics, coupling of evolutionary methods and neural networks in mechanics, methods of artificial intelligence in mechanics based on evolutionary approaches and other unconventional applications in mechanics. Research workers, specialists and professionals who deal with methods of artificial intelligence, especially in the field of evolutionary computation, structural and multidisciplinary optimization would be interested in this book.

Table of Contents

  • Preface. Committee and Sponsors. Evolutionary computation in crack problems
  • W. Beluch. Investigation of evolutionary algorithm effectiveness in optimal synthesis of certain mechanisms
  • K. Bia as-Hetltowski, et al. Minimum heat losses subjected to stiffness constraints: window frame optimization
  • R.A. Bia ecki, M. Krol. Evolutionary computation in inverse problems
  • T. Burczy ski, et al. Hang-glider wing design by genetic optimization
  • S. D'Angelo, et al. An error function for optimum dimension synthesis of mechanisms using genetic algorithms
  • I.F. de Bustos, et al. Evolutionary computation in thermoelastic problems
  • A. D ugosz. Management of evolutionary MAS for multiobjective optimisation
  • G. Dobrowalski, M. Kisiel-Dorohinicki. PAMUC: a new method to handle with constraints and multiobjectivity in evolutionary algorithms
  • R. Filomeno Coelho, et al. A comparative analysis of "controlled elitism" in the NGSA-II applied to frame optimization
  • D. Greiner, et al. IS-PAES: multiobjective optimization with efficient constraint handling
  • A. Hernandez Aguirre, et al. Optimization of aligned fiber laminate composites
  • Z. Hu, et al. Genetic algorithm for damage assessment
  • V.T. Johnson, et al. Estimation of parameters for a hydrodynamic transmission system mathematical model with the application of genetic algorithm
  • A. Kesy, et al. Study of safety of high-rise buildings using evolutionary search
  • S. Khajhpour, D.E. Grierson. Structural design using genetic algorithm
  • E. Kita, et al. The topology optimization using evolutionary search
  • G. Kokot, P. Orantek. Identification of CMM parametric errors by hierarchical genetic strategy
  • J. Ko odziej, et al. Genetic algorithm for fatigue crack detection in Timoshenko beam
  • M. Krawczuk, et al. Multicriteria design optimization of robot gripper mechanisms
  • S. Krenich. Optimal design of multiple clutch brakes using a multistage evolutionary method
  • S. Krenich, A. Osyczka. Distributed evolutionary algorithms in optimization of nonlinear solids
  • W. Kus, T. Burczy ski. Adaptive penalty strategies in genetic search for problems with inequality and equality constraints
  • C.-Y. Lin, W.-H. Wu. On the identification of linear elastic mechanical behaviour of orthopedic materials using evolutionary algorithms
  • M. Magalhaes Dourado, et al. Ranking pareto optimal solutions in genetic algorithm by using undifferentiation interval method
  • J. Montusiewicz. The effectiveness of probabilistic algorithms in shape and topology discrete optimisation of 2-D composite structures
  • A. Muc. Genetic algorithms in optimisation of resin hardening technological processes
  • A. Muc, P. Saj. Hybrid evolutionary algorithms in optimization of structures under dynamical loads
  • P. Orantek. Evolutionary optimization system (EOS) for design automation
  • O. Osyczka, et al. Evolutionary method for a universal motor geometry optimization
  • G. Papa, B. Korou i -Seljak. A review of the development and application of cluster oriented genetic algorithms
  • I.C. Parmee. Genetic algorithm optimization of hole shapes in a perforated elastic plate over a range of loads
  • S. Vigdergauz. An object oriented library for evolutionary programs with applications in partitioning of finite element meshes
  • J. ola, et al.

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