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

Hasançebi O.

COMPUTERS & STRUCTURES, vol.86, pp.119-132, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 86
  • Publication Date: 2008
  • Doi Number: 10.1016/j.compstruc.2007.05.012
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.119-132
  • Keywords: structural optimization, evolutionary algorithms, adaptive evolution strategies (ESs), adaptive penalty function, size/shape optimum design of trusses, truss bridge design, OF-THE-ART, GENETIC ALGORITHMS, SPACE STRUCTURES, DESIGN
  • Middle East Technical University Affiliated: Yes


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. (C) 2007 Elsevier Ltd. All rights reserved.