Journal of KSNVE (소음진동)

The Korean Society for Noise and Vibration Engineering (한국소음진동공학회)
권호 표지

A Study on the Support location Optimizations of the Beams using the Genetic Algorithm and the Sensitivity Analysis.

민감도가 고려된 유전 알고리듬을 이용한 보 구조물의 지지점 최적화에 관한 연구

  • 이재관 (서울대학교 정밀기계설계 공동연구소) ;
  • 신효철 (서울대학교 공과대학 기계항공공학부)
  • Published : 2000.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

This describes a study on the support location optimizations of the beams using the genetic algorithm and the sensitivity analysis. The genetic algorithm is a probabilistic method searching the optimum at several points simultaneously and requiring only the values of the object and constraint functions. It has therefore more chances to find the global solution and can be applied to the various problems. Nevertheless, it has such a shortcoming that it takes too many calculations, because it is ineffective in local search. While the traditional method using sensitivity analysis is of great advantage in searching the near optimum. thus the combination of the two techniques will make use of the individual advantages, that is, the superiority in global searching form the genetic algorithm and that in local searching form the sensitivity analysis. In this thesis, for the practical applications, the analysis is conducted by FEB ; and as the shapes of structures are taken as the design variation, it requires re-meshing for every analysis. So if it is not properly controlled, the result of the analysis is affected and the optimized solution amy not be the real one. the method is efficiently applied to the problems which the traditional methods are not working properly.

Keywords

References

  1. Design Sensitivity Anaysis of Structural Systems Haug, E. J.;Choi, K. K.;Komkov V.
  2. Computers & Structures v.58 no.4 Application of Genetic Algorithm for the Support Location Optimization of Beams Wang, B. P.;Chen, J. L.
  3. Int. J. Solids Structures v.13 On Single and Bimodal Optimum Buckling Loads of Clamped Columns Olhoff. N.;Rasmussen, J.
  4. Optimization of Distributed Parameter Structures v.1 Optimization of structures with repeated Eigenvalues Choi, K. K.;Haug, E. J.
  5. Applied Optimal Design: Mechanical and Structural Systems Arora, J. S.
  6. Structural Optimization v.9 Global Optimization Method for Engineering Applications; A Review Arora, J. S.;Elwakeil, O. A.;Chajande A. I.
  7. Handbook of Genetic Algorithms Davis, L.
  8. Genetic Algorithms in Search, Optimization & Machine Learning Goldberg, D. E.
  9. Int. J. for Numerical Methods in Engineers v.39 Genetic Algorithms as an Approach to Optimize Real-World Trusses Galante, M.
  10. IEEE International Conference on Evolutionary Computation v.1 Accelerated Genetic Algorithms : Combined with Local Search Techniques for Fast and Accurate Global Search Chu K. C.;Gang F.
  11. Schwefel and M$\"{a}$nner(19) Different Learning Algorithms for Neural Networks-A Comparative Study Heistermann J.
  12. Ph. D. Thesis Optimum Frequency Design of Structural Elements Johnson, M. R.
  13. J. Structural Mechanics v.8 Design Sensitivity Analysis in Structural Mechanics Ⅱ: Eigenvalue Variations Haug. E. J.;Rousselet. B.
  14. Structural Optimization v.8 Review Paper ; Multiple Eigenvalues in Structural Optimization Problems Seyraman, A. P.;Lund E.;Olhoff N.
  15. Adaptation in Natural and Artificial Systmes Holland, J. H.
  16. J. of Computers in Civil Engineering v.2 no.2 Genetic Algorithms in Pipeline Optimization Goldberg, D. E.;Kuo, C. H.
  17. The Structural Engineer v.69 no.24 Structural Optimization with the Genetic Algorithm Jenkins M.
  18. MIT CADlab-Technical Report Multimodal Optimization using Genetic Algorithms Gr$\"{u}$ningerr, T.;Wallace, D.
  19. Parallel Problem Solving from Nature-PPSN Ⅲ Davidor, Y.;Schwefel, H. P.;M$\"{a}$nner R.(Eds.)
  20. Solid Mechanics: A Variatinal Approach Dym, C. L.;Shames, I. H.
  21. 경계조건 최적화를 위한 설계 민감도 해석 및 응용 손재흥