Volume 15, Issue 3 (8-2025)
IJOCE 2025, 15(3): 485-510 |
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Kaveh A, Hosseini S, Biabani Hamedani K. OPTIMAL DESIGN OF LARGE-SCALE DOME STRUCTURES WITH MULTIPLE FREQUENCY CONSTRAINTS USING PLASMA GENERATION OPTIMIZATION. IJOCE 2025; 15 (3) :485-510
URL: http://ijoce.iust.ac.ir/article-1-651-en.html
URL: http://ijoce.iust.ac.ir/article-1-651-en.html
1- School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract: (1853 Views)
This paper presents the application of the Plasma Generation Optimization (PGO) algorithm to the optimal design of large-scale dome trusses subjected to multiple frequency constraints. Such problems are notoriously challenging due to their highly non-linear and non-convex nature, characterized by numerous local optima. PGO is a physics-inspired metaheuristic that simulates the processes of excitation, de-excitation, and ionization in plasma generation, balancing global exploration and local refinement through its unique search mechanisms. The performance of PGO is evaluated on three well-established dome truss benchmarks: a 52-bar, a 120-bar, and a 600-bar structure, encompassing both sizing and sizing-shape optimization. A comprehensive statistical analysis based on multiple independent runs demonstrates the algorithm's effectiveness and robustness. The results show that PGO achieves the best-reported minimum weight for the 120-bar and 600-bar domes, while obtaining a highly competitive, near-optimal design for the 52-bar dome. Furthermore, PGO consistently produced low average weights across all problems, confirming its reliability. The convergence histories further validate the algorithm's efficiency in locating feasible, high-quality designs. The findings conclusively establish PGO as a powerful and reliable optimizer for handling complex structural optimization problems with dynamic constraints.
Keywords: structural optimization, frequency constraints, truss structures, metaheuristic algorithms, Plasma generation optimization
Type of Study: Research |
Subject:
Optimal design
Received: 2025/08/27 | Accepted: 2025/10/21 | Published: 2025/10/24
Received: 2025/08/27 | Accepted: 2025/10/21 | Published: 2025/10/24
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