Computational & Technology Resources
an online resource for computational,
engineering & technology publications
Civil-Comp Proceedings
ISSN 1759-3433
CCP: 16
NEURAL NETWORKS & COMBINATORIAL OPTIMIZATION IN CIVIL & STRUCTURAL ENGINEERING
Edited by: B.H.V. Topping and A.I. Khan
Paper VI.4

Application of the Genetic Algorithm to the Multi-Objective Design of Retaining Wall Structures

H. Sugimoto*, H. Yamamoto*, T. Sasaki+ and J. Mitsuo+

*Muroran Institute of Technology, Muroran, Japan
+Civil Engineering & Design Department, Tokyu Construction Co, Ltd., Tokyo, Japan

Full Bibliographic Reference for this paper
H. Sugimoto, H. Yamamoto, T. Sasaki, J. Mitsuo, "Application of the Genetic Algorithm to the Multi-Objective Design of Retaining Wall Structures", in B.H.V. Topping, A.I. Khan, (Editors), "Neural Networks & Combinatorial Optimization in Civil & Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 127-136, 1993. doi:10.4203/ccp.16.6.4
Abstract
The design optimization of retaining wall structures is studied using GA. The design variables of this design problem are the vertical positions of the waling beams and the horizontal interval of the cross beams. These are essentially continuous variables, but are treated as discrete variables in this paper. As ready-made steel products are used for the structural members, the construction cost, which is one of the objective functions of this study, is discontinuous with respect to the design variables. The basic requirements for these types of the structures are not only the construct ion cost, but also the structural security and workability. In addition, this method is applicable to the longitudinal changes in geological conditions. So the design problem is formulated as a discrete multi-objective design problem, and the modified GA is applied to the problem. The results of the numerical examples show the utility of the method described in this paper.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description