An Adaptive Approach to Adjust Constraint Bounds and its Application in Structural Topology Optimization

G. L. Yi () and Y. K. Sui ()
Additional contact information
G. L. Yi: Beijing University of Technology
Y. K. Sui: Beijing University of Technology

Journal of Optimization Theory and Applications, 2016, vol. 169, issue 2, No 15, 656-670

Abstract: Abstract Two difficult situations often occur in the final results of engineering design optimization problems, i.e., final results yielding (1) violated constraints, or (2) no active constraints. In order to avoid these situations, this paper proposes an adaptive approach of dynamically adjusting constraint bounds to address constraint satisfaction issues. Based on the ratio of the true value of the constraint obtained by the analytical formula or finite element analysis, to the corresponding constraint bound used in the current iteration, a new constraint bound is computed and updated automatically for next iteration. By means of controlling the iterative process, this approach is able to make all constraints satisfied at the optimum point. It is implemented successfully and robustly into structural topology optimization problems with a displacement constraint.

Keywords: Structural optimization; Approximated explicit models; Constraint satisfaction issues; An adaptive approach of dynamically adjusting constraint bounds; Structural topology optimization; 93B40 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10957-014-0611-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:169:y:2016:i:2:d:10.1007_s10957-014-0611-x

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-014-0611-x

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().