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Computational Science, Engineering & Technology Series
ISSN 1759-3158
Edited by: M. Papadrakakis, B.H.V. Topping
Chapter 10

Innovative Computational Methods for Structural Optimization

M. Papadrakakis+, Y. Tsompanakis+, N.D. Lagaros+, E. Hinton*, J. Sienz*, G. Thierauf# and J. Cai#

+Institute of Structural Analysis and Seismic Research, National Technical University of Athens, Greece
*Department of Civil Engineering, University of Wales, Swansea, United Kingdom
#Department of Civil Engineering, University of Essen, Germany

Full Bibliographic Reference for this chapter
M. Papadrakakis, Y. Tsompanakis, N.D. Lagaros, E. Hinton, J. Sienz, G. Thierauf, J. Cai, "Innovative Computational Methods for Structural Optimization", in M. Papadrakakis, B.H.V. Topping, (Editors), "Innovative Computational Methods for Structural Mechanics", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 10, pp 195-222, 1999. doi:10.4203/csets.1.10
The objective of this paper is to investigate the efficiency of combinatorial optimization methods and in particular algorithms based on evolution strategies, when incorporated into structural optimization problems. Evolution strategies algorithms are used either on a stand-alone basis, or combined with a conventional mathematical programming technique. Furthermore, the structural analysis phase is replaced by a neural network prediction for the computation of the necessary data for the ES optimization procedure. Advanced domain decomposition techniques is also proposed particularly tailored for parallel solution of large-scale sensitivity analysis problems.

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