Topology and shape optimization of continuum structures by genetic algorithm and BEM

  • Eisuke Kita Nagoya University
  • Tatsuhiro Tamaki Nagoya University
  • Hisashi Tanie Nagoya University

Abstract

This paper describes the topology and shape optimization scheme of continuum structures by using genetic algorithm (GA) and boundary element method (BEM). The structure profiles are defined by using the spline function surfaces. Then, the genetic algorithm is applied for determining the structure profile satisfying the design objectives and the constraint conditions. The present scheme is applied to minimum weight design of two-dimensional elastic problems in order to confirm the validity.

Keywords

Topology and shape optimization, genetic algorithm (GA), boundary element method, spline function, two-dimensional elastic problem.,

References

[1] D. E. Goldberg. Genetic algorithms in search, optimization and machine learning. Addison Wesley, 1 edition, 1989.
[2] L. Davis. Handbook of Genetic Algorithms. Van Nostrand Reinhold, 1 edition, 1991.
[3] J . Sakamoto, J. Oda. A technique of optimal layout design for truss structures using genetic algorithm. In Proc. 34th AIAA/ASME/ASCE/AHS/ASC Struc. Struc. Dyna. Mat. Conf., 2402- 2408, 1993.
[4] E. Kita, H. Tanie. Shape optimization of continuum structures by using genetic algorithm and boundary element method. Engineering Analysis with Boundary Elements: Special Issue, Optimization and Sensitivity Analysis with Boundary Elements, 19: 129- 136, 1997.
[5] Y. Kohama, T. Takada, N. Kozawa, A. Miyamura. Collapse analysis of rigid frame by genetic algorithm. In S. Hernandez and C. A. Brebbia, (Eds.), Computer Aided Optimum Design of Structures V (Proc. 5th International Conference on Computer Aided Optimum Design of Structures, Rome, Italy, 1997), 193- 202, 1997.
Published
Jan 18, 2023
How to Cite
KITA, Eisuke; TAMAKI, Tatsuhiro; TANIE, Hisashi. Topology and shape optimization of continuum structures by genetic algorithm and BEM. Computer Assisted Methods in Engineering and Science, [S.l.], v. 11, n. 1, p. 63-75, jan. 2023. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/1044>. Date accessed: 22 dec. 2024.
Section
Articles

Most read articles by the same author(s)