论文部分内容阅读
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.
In order to improve the accuracy and speed of multi-objective particle swarm optimization (PSO) in multi-objective optimization of structure, a new multi-objective algorithm named MHGHA is proposed based on heuristic particle swarm optimization and genetic algorithm For the study of the reticulated shell structure, the time-history response of the reticulated shell under earthquake is analyzed, and the multi-objective optimization design is carried out with the objective of minimizing the maximum displacement and the lightest structure of the structure. The results show that , The hybrid algorithm has higher convergence accuracy and can achieve multi-objective optimization of complex space structures.