一种基于SAPSO-DE混合算法的结构非概率可靠性优化设计  

Structural non-probabilistic reliability optimization design based on a SAPSO-DE hybrid algorithm

作　　者：郑灿赫 孟广伟[1] 李锋[1] 孔英秀[1] 金耿日 

机构地区：[1]吉林大学机械科学与工程学院,吉林长春130025 [2]理科大学力学学院 [3]吉林大学汽车仿真与控制国家重点实验室,吉林长春130025

出　　处：《中南大学学报（自然科学版）》2015年第5期1628-1634,共7页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(51305157);吉林省科技厅基金资助项目(201205011;201215048)~~

摘　　要：针对不确定性结构的非概率可靠性优化问题,提出一种基于模拟退火粒子群算法和差分进化算法(SAPSODE混合算法)的结构非概率可靠性优化设计方法。考虑结构非概率可靠性指标约束,建立最小化结构体积为目标的优化模型。为了提高结构非概率可靠性优化问题的计算精度和效率,采用基于认知经验进化的SAPSO-DE混合算法进行非概率可靠性优化设计。研究结果表明:基于SAPSO-DE混合算法的结构非概率可靠性优化设计方法克服了PSO算法的早熟现象,并提高了收敛速度和精度;该方法的全局搜索能力强,且具有较强的稳定性。In order to solve the non-probabilistic reliability optimization problems of the uncertain structure, a structural non-probabilistic reliability optimal design method based on the hybrid algorithm of the simulated annealing-particle swarm optimization algorithm and the differential evolution algorithm（SAPSO-DE hybrid algorithm） was proposed.Considering the constraints of the structural non-probabilistic reliability index, the optimization model was established to minimize the structural volume. In order to improve the computational accuracy and efficiency of the structural non-probabilistic reliability, a non-probabilistic reliability optimization design was carried out based on the SAPSO-DE hybrid algorithm of the cognitive experience evolution. The results show that the non-probabilistic reliability optimization design method of structure based on the SAPSO-DE hybrid algorithm overcomes the premature phenomenon of the PSO algorithm and improves the convergence speed and precision, and the global search ability of this method is strong and has strong stability.

关 键 词：非概率可靠性指标 凸模型 不确定性 粒子群优化算法 差分进化算法 模拟退火 

分 类 号：TB114.3[理学—概率论与数理统计] TB21[理学—数学]