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首页> 外文期刊>Arabian Journal for Science and Engineering. Section A, Sciences >Performance Comparison of Metaheuristic Algorithms for the Optimal Design of Space Trusses
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Performance Comparison of Metaheuristic Algorithms for the Optimal Design of Space Trusses

机译：空间桁架优化设计的元启发式算法性能比较。

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摘要

In this study, eight population-based metaheuristic algorithms were employed for the design of truss structures with continuous design variables. The selected algorithms were genetic, ant colony, particle swarm, artificial bee colony, gravitational search, firefly, gray wolf optimization and Jaya. The purpose was to objectively evaluate the performance of these algorithms under the same conditions and select the best efficient algorithm by assessing three example truss structures. The results obtained from the examples showed that the algorithms were both computationally efficient and robust when the number of design variables was approximately 10 and a significant number of iterations were performed. When the number of design variables was increased to 53, artificial bee colony, Jaya and gray wolf optimization were found to be computationally more effective than the remaining algorithms.
机译：在这项研究中，使用八种基于人口的元启发式算法来设计具有连续设计变量的桁架结构。选择的算法是遗传，蚁群，粒子群，人工蜂群，引力搜索，萤火虫，灰太狼优化和贾亚。目的是客观地评估这些算法在相同条件下的性能，并通过评估三个示例桁架结构来选择效率最高的算法。从示例中获得的结果表明，当设计变量的数量大约为10且执行了大量迭代时，该算法在计算上既有效又健壮。当设计变量的数量增加到53个时，发现人工蜂群，Jaya和灰太狼优化在计算上比其余算法更有效。

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