Enhancing particle swarm optimization algorithm using two new strategies for optimizing design of truss structures

Y. C. Lu, J. C. Jan, Shih-Lin Hung*, G. H. Hung

*此作品的通信作者

研究成果: Article同行評審

29 引文 斯高帕斯(Scopus)

摘要

This work develops an augmented particle swarm optimization (AugPSO) algorithm using two new strategies,: boundary-shifting and particle-position- resetting. The purpose of the algorithm is to optimize the design of truss structures. Inspired by a heuristic, the boundary-shifting approach forces particles to move to the boundary between feasible and infeasible regions in order to increase the convergence rate in searching. The purpose of the particle-position-resetting approach, motivated by mutation scheme in genetic algorithms (GAs), is to increase the diversity of particles and to prevent the solution of particles from falling into local minima. The performance of the AugPSO algorithm was tested on four benchmark truss design problems involving 10, 25, 72 and 120 bars. The convergence rates and final solutions achieved were compared among the simple PSO, the PSO with passive congregation (PSOPC) and the AugPSO algorithms. The numerical results indicate that the new AugPSO algorithm outperforms the simple PSO and PSOPC algorithms. The AugPSO achieved a new and superior optimal solution to the 120-bar truss design problem. Numerical analyses showed that the AugPSO algorithm is more robust than the PSO and PSOPC algorithms.

原文English
頁(從 - 到)1251-1271
頁數21
期刊Engineering Optimization
45
發行號10
DOIs
出版狀態Published - 1 10月 2013

指紋

深入研究「Enhancing particle swarm optimization algorithm using two new strategies for optimizing design of truss structures」主題。共同形成了獨特的指紋。

引用此