中文摘要：

为了改善多目标粒子群算法在结构多目标优化中的收敛精度和速度,提出了一种新型多目标算法——基于启发式粒子群算法和遗传算法的多目标杂交算法（MHGHA）.以双层网壳结构为研究对象,对其在地震作用下的时程响应进行分析,以结构节点最大位移最小化和结构质量最轻化为目标进行多目标优化设计,并与经典算法进行对比.结果表明,杂交算法的收敛精度更高,同时能够实现复杂空间结构多目标优化.

英文摘要：

A new multi-objective algorithm—Multi-objective HPSO-GA Hybrid Algorithm（MHGHA）,based on multi-objective particle swarm algorithm,was presented in this paper to improve convergence precision and speed of multi-objective optimization tasks. The minimizing of the maximum node displacement and weight of a double-layer spherical shell structure under earthquake action was considered as two optimization objectives of the design.The time-history analysis results show that the hybrid algorithm has higher convergence precision than the classical multi-objective algorithms,and it is able to deal with the multi-objective optimal design of complex spatial structures.