標題: Enhancing particle swarm optimization algorithm using two new strategies for optimizing design of truss structures
作者: Lu, Y. C.
Jan, J. C.
Hung, S. L.
Hung, G. H.
土木工程學系
Department of Civil Engineering
關鍵字: truss structures;stochastic search method;optimization design;particle swarm optimization (PSO)
公開日期: 1-Oct-2013
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.
URI: http://dx.doi.org/10.1080/0305215X.2012.729054
http://hdl.handle.net/11536/23004
ISSN: 0305-215X
DOI: 10.1080/0305215X.2012.729054
期刊: ENGINEERING OPTIMIZATION
Volume: 45
Issue: 10
起始頁: 1251
結束頁: 1271
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