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Optimization of truss structures with two archive-boosted MOHO algorithm
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DOI：10.1016/j.aej.2025.02.032.png)
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摘要
En 中文
This study identifies the Two-Archive Multi-Objective Hippopotamus Optimization Algorithm (MOHO2Arc) as an advanced multi-objective optimization method for optimizing five widely recognized truss structures. The primary objectives are to minimize the structures' mass and maximum nodal displacement. MOHO2Arc improves upon the standard Multi-Objective Hippopotamus Optimization (MOHO) by incorporating a two-archive strategy, significantly boosting solution diversity and optimization efficiency. A thorough comparative analysis was performed to evaluate the performance of the MOHO2Arc against other established multi-objective optimization algorithms. Performance metrics were applied to assess each algorithm's ability to generate diverse, high-quality solutions. The results demonstrate that MOHO2Arc substantially improves solution diversity and quality. Moreover, statistical analysis using Friedman's test further confirms that MOHO2Arc consistently outperforms the other algorithms in optimization tasks. This research highlights MOHO2Arc as an efficient and promising multi-objective truss structure optimization approach, offering notable advancements over current state-of-theart techniques.
Keyword:
Dual-archive strategy
Truss structural optimization
Pareto dominance
Diversity and Swarm analysis
Convergence behavior
期刊
IF:
6.8
论文数:
6.3K
被引数:
2.6W
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