دوره 15، شماره 3 - ( 5-1404 )
جلد 15 شماره 3 صفحات 445-419 |
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Paknahad M, Hosseini P, Kaveh A. PARAMETER-FREE STRUCTURAL OPTIMIZATION OF DOME TRUSSES: DEVELOPMENT AND APPLICATION OF THE SA_EVPS ALGORITHM WITH STATISTICAL LEARNING MECHANISMS. IJOCE 2025; 15 (3) :419-445
URL: http://ijoce.iust.ac.ir/article-1-647-fa.html
URL: http://ijoce.iust.ac.ir/article-1-647-fa.html
PARAMETER-FREE STRUCTURAL OPTIMIZATION OF DOME TRUSSES: DEVELOPMENT AND APPLICATION OF THE SA_EVPS ALGORITHM WITH STATISTICAL LEARNING MECHANISMS. عنوان نشریه. 1404; 15 (3) :419-445
چکیده: (283 مشاهده)
This study presents the application of the Self-Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm for large-scale dome truss optimization under frequency constraints. SA-EVPS incorporates self-adaptive parameter control, memory-based learning mechanisms, and statistical regeneration strategies to overcome limitations of traditional metaheuristic algorithms in structural optimization. The algorithm's performance is evaluated on three benchmark dome structures: (1) a 600-bar single-layer dome with 25 design variable groups, (2) an 1180-bar single-layer dome with 59 design variable groups, and (3) a 1410-bar double-layer dome with 47 design variable groups, all subject to natural frequency constraints. Comparative analysis against five state-of-the-art algorithms—Dynamic Particle Swarm Optimization (DPSO), Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO), Vibrating Particles System (VPS), and Enhanced Vibrating Particles System (EVPS)—demonstrates SA-EVPS's superior convergence characteristics and solution quality. Results show that SA-EVPS consistently achieves the lowest structural weights with remarkable stability across all test cases. The algorithm's self-adaptive mechanisms eliminate manual parameter tuning while the statistical regeneration mechanism prevents premature convergence in large-scale optimization problems. This research establishes SA-EVPS as a robust and efficient metaheuristic for frequency-constrained structural optimization of complex dome structures.
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