733
Views
40
CrossRef citations to date
0
Altmetric
Original Articles

Enhanced particle swarm optimization for size and shape optimization of truss structures

, , &
Pages 1939-1956 | Received 07 Jun 2016, Accepted 06 Dec 2016, Published online: 17 Jan 2017
 

ABSTRACT

This article presents an enhanced particle swarm optimization (EPSO) algorithm for size and shape optimization of truss structures. The proposed EPSO introduces a particle categorization mechanism into the particle swarm optimization (PSO) to eliminate unnecessary structural analyses during the optimization process and improve the computational efficiency of the PSO-based structural optimization. The numerical investigation, including three benchmark truss optimization problems, examines the efficiency of the EPSO. The results demonstrate that the particle categorization mechanism greatly reduces the computational requirements of the PSO-based approaches while maintaining the original search capability of the algorithms in solving optimization problems with computationally cheap objective function and expensive constraints.

Disclosure statement

There are no conflicts of interest.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities [grant number WUT: 2015IVA015] and the National Natural Science Foundation of China [grant number 51408249].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,161.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.