基于改进ACMPSO 并行算法的土石坝本构参数反演

针对一般的优化算法进行土石坝本构参数反演时收敛速度慢,且容易陷入局部最优的问题,引入动态变异系数和OpenMP并行指令,对自适应混沌变异粒子群算法(ACMPSO)进行改进,并采用实例对改进算法进行了验证。实例验证结果表明,与一般优化算法相比,改进的ACMPSO并行算法能够有效避免算法陷入局部最优的问题,大幅降低计算耗时,具有收敛速度快、反演精度高、稳定性好等特点,适用于处理高维度、计算量庞大的复杂参数反演问题。

Inversion of constitutive parameters of earth-rock dams based on improved ACMPSO parallel algorithm

To solve the problem of slow convergence speed and easy falling into local optimum for general optimization algorithms during parameter inversion of constitutive parameters of earth-rock dams, the adaptive chaotic mutation particle swarm optimization(ACMPSO)algorithm was improved by using dynamic variation coefficient and OpenMP parallel instructions, and the improved ACMPSO algorithm was validated by a case. The results demonstrate that the improved ACMPSO parallel algorithm can effectively prevent algorithm from falling into local optimum and reduce the calculation time significantly. The algorithm has the characteristics of fast convergence, high inversion accuracy and good stability, which is suitable to solve complex parameter inversion problems with high dimensions and huge computation.