改进的非概率可靠性全局最优解方法

对于非概率可靠度的求解，改进的一维优化算法计算简便但仅能搜索到部分可能失效点，全局最优解法可搜索所有可能失效点但计算量过大。鉴于此种情况，本文将改进的一维优化算法与全局最优解法相结合，吸收两种方法的优点提出改进的全局最优解法。提出的方法通过变量的单调性来确定变量的取值，在不遗漏可能失效点的前提下，减少根值方程组的数目，从而降低计算量，提高计算效率。通过算例分析，证明了提出的改进的全局最优解法的有效性和可行性。

Improved Global Optimization Method of Solving Non-probabilistic Reliability

To solve non-probabilistic reliability, the improved one-dimensional optimization algorithm can be easily used, which, however, only searches part of the probable failure points. The global optimization method, on the other hand, although capable of searching all the probable failure points, requires a large amount of calculation. In view of such situation, an improved global optimization method is proposed in this study by combining the improved one-dimensional optimization algorithm with the global optimization method. The presented method possesses the advantages of both the improved one-dimensional optimization algorithm and the global optimization method, by means of which, the values of variables are determined based on the monotonicity of variables. Without losing any probable failure points, this method is contributive to reducing the number of extreme point equations, lowering the computational complexity, and improving the computational efficiency. The effectiveness and feasibility of the presented method are verified by examples.