基于广义遗传算法的结构动力响应优化

DYNAMIC RESPONSE OPTIMIZATION BASED ON GENERALIZED GENETIC ALGORITHM

为提高广义遗传算法的收敛效率,提出了防止遗传算法发生早熟收敛的异种机制,给出了一个判断种群近亲繁殖程度的判别式和两种选择异种的方法,并结合种群隔离机制、算术杂交、自适应随机变异等数值方法设计了新的广义遗传算法。将该算法应用于结构动力响应的支撑位置优化问题。数值算例表明:异种机制能够明显提高遗传算法的收敛效率,并有效防止早熟收敛;带有异种机制的新广义遗传算法能够解决具有抗弯刚度的结构动力响应支撑位置优化问题,对于求解复杂的结构动力响应支撑位置优化具有较强的适用性。

To improve the accuracy and convergence efficiency of the generalized genetic algonmm, heterogeneity strategy is proposed firstly to avoid inbreeding and premature. Furthermore, an expression to estimate the extent of inbreeding and two methods for selecting heterogeneity were given. A new generalized genetic algorithm was presented in this paper. Many new techniques such as population isolation, arithmetical crossover and adaptive random mutation were used. This method was used for support-position optimization of structure dynamic response. Numerical examples demonstrated that heterogeneous strategy can improve the convergence efficiency and avoid premature effectively. The new generalized genetic algorithm can optimize the support positions when both elastic and bending rigidity are considered. It has extensive applicability in complicated support-position optimization problem of dynamic response.