基于改进的遗传模拟退火算法的钢框架优化设计

将遗传算法的全局寻优性能好和模拟退火的局部搜索能力强的优点相结合,提出了用于钢框架优化设计的遗传模拟退火算法,并对其进行了改进。在遗传算法部分提出了基于阈值的动态交叉、变异概率,并且采用联赛精英选择策略和最优保存策略,在种群的整体适应度提高的同时,增强了进化后期的种群多样性,提高了算法的收敛速度。在退火部分,针对钢框架优化的具体问题提出了一种更加紧凑灵活的邻域结构,提高了算法寻优性能。最后,将改进的算法用于工程实例,并与其他优化方法相比较,结果表明,该改进算法是一种用于钢框架结构优化设计的更加行之有效的方法。

STEEL FRAME STRUCTURAL OPTIMIZATION DESIGN BASED ON IMPROVED GENETIC SIMULATED ANNEALING ALGORITHM

It is applied genetic simulated annealing algorithm(SAGA)to solving the steel frame structural optimization.A new adaptive crossover and mutation operator based on threshold was presented in the genetic part.It is also given a novel compact local searching method in the simulated part.SAGA has the global searching ability together with the local fast converging ability.The experiments indicate SAGA can improve the evolution speed and the abilities of seeking the global excellent result.