基于快速非支配排序遗传算法的阻尼器多目标优化布置

Multi-objective optimal arrangement of dampers based on nondominated sorting genetic algorithm-Ⅱ

将快速非支配排序遗传算法(NSGA-Ⅱ)和并行遗传算法相结合,提出内嵌NSGA-Ⅱ的粗粒度-主从式并行遗传算法。该算法将种群分为多个子种群,每个子种群可独立并行执行NSGA-Ⅱ操作;达到迁移周期时,子种群之间执行迁移操作;完成迁移后,子种群再次独立并行执行NSGA-Ⅱ操作。以最大层间位移角和最大楼层加速度为目标函数,对14层消能减震钢框架结构上的阻尼器布置位置进行优化分析。结果表明:该算法既实现多目标优化,又提高优化速度;对比常规隔层布置方法,该算法可使结构的层间位移角减震系数和加速度减震系数分别至少提高16.82%和16.01%。

A coarse-grained-master-slave parallel genetic algorithm with NSGA-Ⅱ embedded is proposed by combining nondominated sorting genetic algorithm-Ⅱ and parallel genetic algorithm.According to the algorithm,a population is divided into several sub-populations,which can independently complete the operation of NSGA-Ⅱ in parallel.If the migration cycle is reached,the sub-populations perform the migration operation.After the migration is completed,each sub-population independently complete the operation of NSGA-Ⅱ in parallel again.A 14-story energy dissipation steel frame structure is selected as the research object,and the optimal design of damper arrangement is conducted by taking maximal inter-story drift ratio and maximal floor acceleration as the control objective.The results show that the algorithm not only achieves multi-objective optimization,but also improves the optimization speed;Compared with the results of the structure with the dampers placed in every two storeys,shock absorption coefficient of inter-story drift ratio and floor acceleration of the structure equipped with the new algorithm can be increased by 16.82%and 16.01%.