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Reliability analysis of geostructures based on metaheuristic optimization

机译：基于元启发式优化的岩土结构可靠性分析

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The objective of this work is to incorporate metaheuristic optimization into the framework of the reliability analysis of geostructures in conjunction with innovative tools for treating computational intensive problems of real-world geostructural systems. For the purposes of this study two types of random variables are considered: those which influence demand and those that affect capacity. The Monte Carlo simulation method is considered as the most reliable method for estimating exceedance probabilities or other statistical quantities albeit with excessive, in many cases, computational cost, while first or second order reliability methods (FORM, SORM) constitute alternative approaches. In this study, in order to propose an efficient methodology for performing reliability analysis of geostructures we assess and compare seven metaheuristic optimization algorithms incorporated into FORM for solving reliability analysis problems, while one neural network approximation of the limit-state function is also examined. The results suggest that the seven approaches examined offer applicable as well as fast solutions but with varying qualitative characteristics. (C) 2014 Elsevier B.V. All rights reserved.
机译：这项工作的目的是将元启发式优化方法与用于处理现实世界中的地质结构系统的计算密集型问题的创新工具相结合，将其纳入结构的可靠性分析框架中。为了本研究的目的，考虑了两种类型的随机变量：影响需求的变量和影响容量的变量。蒙特卡罗模拟方法被认为是估计超出概率或其他统计量的最可靠方法，尽管在许多情况下计算成本过高，而一阶或二阶可靠性方法（FORM，SORM）构成了替代方法。在这项研究中，为了提出一种有效的方法来进行结构的可靠性分析，我们评估并比较了FORM中包含的七种启发式优化算法，用于解决可靠性分析问题，同时还研究了极限状态函数的一种神经网络近似方法。结果表明，所研究的七种方法既可以提供适用的解决方案，也可以提供快速解决方案，但具有不同的定性特征。 （C）2014 Elsevier B.V.保留所有权利。

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