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改进的群搜索优化算法在结构优化中的应用
引用本文:张雯雰.改进的群搜索优化算法在结构优化中的应用[J].数字社区&智能家居,2014(5):3106-3110.
作者姓名:张雯雰
作者单位:湘南学院计算机科学系,湖南郴州423000
基金项目:湖南省科技计划项目(NO.2011TP4016-3);湘南学院“十二五”重点学科计算机应用技术学科项目;湘南学院计算机应用技术创新训练中心项目[2012]125号(NO.2)
摘    要:针对桁架结构优化设计问题,对群搜索优化算法(GSO)进行了算法修改和参数调整,并将修改后的算法应用到10杆、17杆和200杆共3个桁架结构截面优化设计算例中,同时与另一种GSO改进算法(IGSO)进行了对比分析。对于每个算例,该文改进算法和IGSO算法各运行了10次,从10次运行的统计结果可以看出,改进算法的优化效果和稳定性均好于IGSO算法。另外,改进算法也与目前结构优化中较好的其它几个算法进行了比较,总体来说,改进算法的最佳优化结果与这些算法的最佳结果相当。

关 键 词:群集智能  群搜索优化算法  结构优化  桁架

Improved Group Search Optimizer Algorithm for Design Optimization of Structures
ZHANG Wen-Fen.Improved Group Search Optimizer Algorithm for Design Optimization of Structures[J].Digital Community & Smart Home,2014(5):3106-3110.
Authors:ZHANG Wen-Fen
Affiliation:ZHANG Wen-Fen (Department of Computer Science, Xiangnan University, Chenzhou 423000, China)
Abstract:An improved Group Search Optimizer algorithm (GSO) is presented for solving structures optimization problems. This paper applied the improved algorithm to 10-bar, 17-bar, and 200-bar truss structures optimal design examples and com-pared with another improved GSO algorithm (IGSO). For each example, the improved algorithm herein and IGSO algorithm is executed 10 times. The statistics show that the results and stability of the improved algorithm are better than that of IGSO. In ad-dition, the improved algorithm is compared with other good algorithms in structure optimization. It can be seen that the best de-sign of the improved algorithm for each example is as good as that of these algorithms.
Keywords:swarm intelligence  group search optimizer algorithm  structural optimization  truss
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