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Computational Science, Engineering & Technology Series
ISSN 1759-3158
Edited by: B.H.V. Topping, L. Lämmer
Chapter 13

Evolutionary Algorithms applied to Structural Optimization Problems

M. Papadrakakis, N.D. Lagaros and G. Kokassalakis

Institute of Structural Analysis and Seismic Research, National Technical University of Athens, Greece

Full Bibliographic Reference for this chapter
M. Papadrakakis, N.D. Lagaros, G. Kokassalakis, "Evolutionary Algorithms applied to Structural Optimization Problems", in B.H.V. Topping, L. Lämmer, (Editors), "High Performance Computing for Computational Mechanics", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 13, pp 207-233, 2000. doi:10.4203/csets.4.13
The objective of this study is to investigate the efficiency of various Evolutionary Algorithms (EAs), such as Evolution Strategies (ESs) and Genetic Algorithms (GAs), when applied to large-scale sizing optimization problems. ESs and GAs imitate biological evolution in nature and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism The proposed methods are compared with a conventional mathematical programming (MP) method. A hybrid methodology. namely GAs-MP is also proposed in order to combine the advantages of both methods. The numerical tests presented demonstrate the computational advantages of the proposed methods which become more pronounced in large-scale optimization problems.

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