Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures

In this study the computational performance of adaptive evolution strategies (ESs) in large-scale structural optimization is mainly investigated to achieve the following objectives: (i) to present an ESs based solution algorithm for efficient optimum design of large structural systems consisting of...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Computers & structures Ročník 86; číslo 1; s. 119 - 132
Hlavný autor: HASANCEBI, O
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Elsevier Ltd 2008
Elsevier Science
Predmet:
ISSN:0045-7949, 1879-2243
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this study the computational performance of adaptive evolution strategies (ESs) in large-scale structural optimization is mainly investigated to achieve the following objectives: (i) to present an ESs based solution algorithm for efficient optimum design of large structural systems consisting of continuous, discrete and mixed design variables; (ii) to integrate new parameters and methodologies into adaptive ESs to improve the computational performance of the algorithm; and (iii) to assess successful self-adaptation models of ESs in continuous and discrete structural optimizations. A numerical example taken from the literature is studied in depth to verify the enhanced performance of the algorithm, as well as to scrutinize the role and significance of self-adaptation in ESs for a successfully implemented optimization process. Besides, the utility of the algorithm for practical structural engineering applications is demonstrated using a bridge design example. It is shown that adaptive ESs are reliable and powerful tools, and well-suited for optimum design of complex structural systems, including large-scale structural optimization.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0045-7949
1879-2243
DOI:10.1016/j.compstruc.2007.05.012