This paper proposes niching importance sampling, a framework that combines concepts from reliability analysis, e.g. Markov chains, importance sampling, and relative cross entropy minimisation, with niching techniques from evolutionary multi-modal optimisation. The result is a highly robust estimator of the probability of failure, that can tackle sampling challenges posed by the underlying geometry of a reliability problem. Niching importance sampling is tested on a range of numerical examples and is shown to consistently avoid the degenerate behaviour observed for existing reliability methods on several multi-modal performance functions.

翻译：本文提出小生境重要性采样框架，该框架将可靠性分析中的概念（如马尔可夫链、重要性采样及相对交叉熵最小化）与进化多模态优化中的小生境技术相结合。其成果是一种高度稳健的失效概率估计器，能够应对可靠性问题潜在几何结构带来的采样挑战。通过一系列数值算例测试，小生境重要性采样被证明能持续避免现有可靠性方法在多模态性能函数上出现的退化行为。