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为解决不确定性结构的非概率可靠性优化存在的问题,提出了一种基于模拟退火粒子群算法与差分进化算法的结构非概率可靠性优化方法。在兼顾结构非概率可靠性指标约束的前提下,构建了最小化结构体积为目标的优化模型。为改善结构非概率可靠性优化问题的计算效率和精度,通过基于认知经验进化的MIXED-EVO混合算法来实施非概率可靠性优化设计。实验结果表明,该算法可避免PSO算法的早熟现象,改善收敛速度和计算精度,具有较好的全局搜索能力,稳定性较强。
In order to solve the problem of non-probabilistic reliability optimization of uncertain structures, a non-probabilistic reliability optimization method based on Simulated Annealing Particle Swarm Optimization and Differential Evolution Algorithm is proposed. On the premise of taking account of the structural non-probabilistic reliability constraints, an optimization model with the objective of minimizing the structural volume is constructed. In order to improve the computational efficiency and accuracy of the structural non-probabilistic reliability optimization problem, the MIXED-EVO hybrid algorithm based on cognitive experience is used to implement the non-probabilistic reliability optimization design. The experimental results show that this algorithm can avoid the premature phenomenon of PSO algorithm, improve the convergence speed and accuracy, have better global search ability and strong stability.