Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm

Mortazavi A., TOĞAN V.

APPLIED SOFT COMPUTING, vol.51, pp.239-252, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51
  • Publication Date: 2017
  • Doi Number: 10.1016/j.asoc.2016.11.032
  • Journal Name: APPLIED SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.239-252
  • Keywords: Particle swarm optimization, Weighted particle, Improved fly-back mechanism, Layout and sizing optimization of truss, structures, LEARNING-BASED OPTIMIZATION, FREQUENCY CONSTRAINTS, SIZE OPTIMIZATION, SHAPE
  • Karadeniz Technical University Affiliated: Yes

Abstract

Natural frequencies offer useful knowledge on the dynamic response of the structures. It is possible to avoid from the destructive effects of dynamic loads on the structures by optimizing layout and size of their subject to constraints on natural frequencies. Since optimization problems including frequency constraints are highly nonlinear, this kind of problems forms a challenging area to test the performance of the different optimization techniques. This study tests the performance of an integrated particle swarm optimization algorithm (iPSO), a new particle swarm optimizer integrated with the improved fly-back mechanism and the weighted particle concept, in four weight minimization of truss structures with sizing and layout variables under multiple frequency constraints. Optimization results demonstrate that the new algorithm is competitive with other state-of-the-art metaheuristic algorithms in dynamic and static structural optimization problems. (C) 2016 Elsevier B.V. All rights reserved.