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A new Newton metaheuristic algorithm for discrete performance-based design optimization of steel moment frames

机译:基于离散性能的基于钢时刻框架设计优化的新牛顿成群质算法

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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. (C) 2020 Elsevier Ltd. All rights reserved.
机译:本文提出了一种新的高效的成群质算法,用于离散性能的基于钢时刻框架的地震设计优化。该拟议的成群质型方法使用基于牛顿梯度的方法作为其基于人口框架的更新方案,因此它被称为牛顿成群质算法(NMA)。为了使NMA能够有效地探索离散设计空间,将找到找到的最佳解决方案的术语添加到算法的基本更新规则中。此外,提出了一种简单而有效的方法,以便在所提出的算法的本地和全球搜索能力之间建立平衡。通过呈现两个基准离散桁架优化问题来说明NMA的效率。此外,在基于性能的设计框架中,在NMA的框架中优化了三个钢时刻帧,并将结果与​​最近的近期的遗传学相比。使用统计参数和非参数测试分析算法的性能,指示NMA优于文献中的其他算法。 (c)2020 elestvier有限公司保留所有权利。

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