广东工业大学学报 ›› 2010, Vol. 27 ›› Issue (2): 27-31.

• 综合研究 • 上一篇    下一篇

改进的群搜索优化算法在桁架结构形状优化设计中的应用

  

  1. 广东工业大学土木与交通工程学院,广东广州510006
  • 出版日期:2010-06-25 发布日期:2010-06-25
  • 作者简介:曾世开(1986-),男,硕士研究生,主要研究方向为结构计算理论及方法
  • 基金资助:

    国家自然科学基金资助(10772052);广东省自然科学基金资助(06104655,8151009001000042)

Application of Improved Group Search Optimizer in Shape Optimization of Truss Structures

  1. Faculty of Civil and Transportation Engineering,Guangdong University ofTechnology ,Guangzhou 510006,China
  • Online:2010-06-25 Published:2010-06-25

摘要: 介绍了两种改进的群搜索优化算法IGSO(Improved Group Search Optimizer)——快速群搜索优化算法QGSO(Quick Group Search Optimizer)与快速被动群搜索优化算法QGSOPC(Quick Group Search Optimizer with Passive Congregation),并应用于离散变量桁架结构形状优化设计,包括平面和空间桁架结构.几个实例计算结果表明两种改进的群搜索优化算法(QGSO与QGSOPC)与GSO算法及已有文献方法相比具有较好的收敛精度和较快的收敛速度,只需较少的迭代次数就能寻找到最优解,并且QGSO与QGSOPC算法程序语句比GSO算法程序语句简略得多,易于编程实现,可应用于工程结构的优化设计.

关键词: 群搜索优化算法;形状优化;桁架;收敛速度;收敛精度;离散变量

Abstract: Two improved group search optimization algorithms(IGSO),quick group search optimization(QGSO) and quick group search optimizer with passive congregation(QGSOPC)algorithm,are presented,and they are applied in shape optimization design of truss structures with discrete variables,including planar trusses and spatial trusses.Several numerical examples are given to test the IGSO algorithms.The optimization results are compared with those of the GSO algorithms and some algorithms in reference.The results show that the IGSO algorithmss have better perform ance in term s of convergence than the GSO algorithm and other algorithms,and can find the optimum solution with less iteration.Besides,compared with that of the GSO algorithm ,the IGSO algorithm program statement is much briefer,and easier to be programmed.It is desirable for IGSO to be used for structural optimal design problems.

Key words: Group search optimizer(GSO);shape optimization;truss;convergence rate;convergence accuracy;discrete variables

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