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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 被引量:1

Application of Improved Group Search Optimizer in Shape Optimization of Truss Structures
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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. 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 performance in terms 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.
出处 《广东工业大学学报》 CAS 2010年第2期27-31,49,共6页 Journal of Guangdong University of Technology
基金 国家自然科学基金资助(10772052) 广东省自然科学基金资助(06104655 8151009001000042)
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 Group search optimizer(GSO) shape optimization truss convergence rate convergence accuracy discrete variables
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