Abstract In this paper a new and efficient metaheuristic algorithm is proposed for discrete performance-based seismic design optimization of steel moment frames. The proposed metaheuristic uses the Newton gradient-based method as its updating scheme in a population-based framework and therefore it is termed as Newton Metaheuristic Algorithm (NMA). In order to enable the NMA to effectively explore the discrete design space, a term containing the best solution found is added to the basic updating rule of the algorithm. In addition, a simple and efficient method is proposed in order to establish a balance between local and global search abilities of the proposed algorithm. The efficiency of the NMA is illustrated by presenting two benchmark discrete truss optimization problems. Moreover, three steel moment frames are optimized in the framework of performance-based design by the NMA and the results are compared with those of some recent metaheuristics. The performance of the algorithms is analyzed using statistical parametric and non-parametric tests indicating that NMA outperforms the other algorithms in literature.

中文翻译：

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基于离散性能的钢力矩框架设计优化新牛顿元启发式算法

摘要 本文提出了一种新的高效元启发式算法，用于基于离散性能的钢矩框架抗震设计优化。所提出的元启发式算法在基于种群的框架中使用基于牛顿梯度的方法作为其更新方案，因此被称为牛顿元启发式算法（NMA）。为了使 NMA 能够有效地探索离散设计空间，在算法的基本更新规则中添加了包含找到的最佳解决方案的项。此外，为了在所提出的算法的局部和全局搜索能力之间建立平衡，提出了一种简单有效的方法。NMA 的效率通过提出两个基准离散桁架优化问题来说明。而且，NMA在基于性能的设计框架中对三个钢力矩框架进行了优化，并将结果与​​一些最近的元启发式方法进行了比较。使用统计参数和非参数测试分析算法的性能，表明 NMA 优于文献中的其他算法。