收稿日期:2019-06-20 修回日期:2019-10-22 网络出版时间:2020-01-10
英译汉在线翻译基金项目：河北省高等学校科学技术研究重点项目(ZD2019114)
作者简介：李彦苍(1974-)，男，博士，教授，博导，研究方向为计算机智能理论及其工程应用；杨宗瑾(1994)，男，研究生，研究方向为计算机智能理
论及其工程应用㊂
网络出版地址:knski /kcms /detail /61.1450.TP.20200110.1118.014.html 基于改进引力搜索算法的桁架结构优化设计
李彦苍，杨宗瑾
(河北工程大学，河北邯郸056038)胆怯
上海美术高中有哪些摘 要：引力搜索算法是近几年提出的较有竞争力的群智能优化算法，然而，标准引力搜索算法存在后期收敛速度慢的缺点㊂为有效利用优化算法来解决结构优化的问题，提出一种改进的引力搜索算法(improved gravitational arch algorithm,IGSA)㊂通过引入Logistic 映射，使GSA 初始种群遍历整个搜索空间，提高算法找出最优解的可能性㊂通过引入粒子群算法(particle swarm optimization,PSO)的信息
maki如果冬天来了 春天还会远吗交互机制，利用个体粒子历史最佳位置和种群历史最佳位置动态调整粒子的速度和位置，使个体粒子更快地向适应度值更高的位置移动，使算法搜索能力加强㊂对6个经典测试函数进行寻优，结果表明改进后算法收敛速度快，收敛精度高，稳定性较佳，跳出局部最佳解的能力较强㊂用IGSA 和GSA 对72杆空间桁架进行尺寸优化，与其他算法相比，结果表明IGSA 得到最优值的迭代次数明显减少，得到的最优解明显优于通用算法㊂
关键词：测试函数；引力搜索算法；自适应；混沌映射；桁架优化
中图分类号:TU323.4 文献标识码:A 文章编号:1673-629X (2020)05-0049-07
女士英文
小娘doi:10.3969/j.issn.1673-629X.2020.05.010
wallstreetOptimization Design of Truss Structure Bad on Improved Gravitational Search Algorithm
LI Yan -cang ,YANG Zong -jin
(Hebei University of Engineering ,Handan 056038,China )
Abstract :The gravitational arch algorithm (GSA )is a competitive swarm intelligence optimization algorithm propod in recent years.However ,the standard gravitational arch algorithm has the dis
advantage of slow convergence in the later stage.In order to effectively solve the problem of structural optimization ,an improved gravity arch algorithm (IGSA )is propod.By introducing Logistic mapping ,the initial GSA population travers the whole arch space and improves the possibility of finding the optimal solution.Through the intro⁃duction of particle swarm optimization (PSO )information interaction mechanism ,the particle speed and position can be dynamically adjusted by using the optimal position of individual particle history and the optimal position of population history ,so that individual particles can move to the position with higher fitness value more quickly ,and the arch ability of the algorithm can be strengthened.Six classical test functions are optimized ,and the results show that the improved algorithm has fast convergence speed ,high convergence accuracy ,high stability and strong ability to jump out of the local optimal solution.IGSA and GSA are ud to optimize the size of the space truss of bar
72.Compared with other algorithms ,the results show that the number of iterations of the optimal value obtained by IGSA is significantly re⁃duced ,and the optimal solution obtained is obviously superior to the general algorithm.
Key words :test function ;gravitational arch algorithm ;adaption ;chaos mapping ;struss optimization 0 引 言
对于桁架结构，在给定结构形式㊁材料和形状的情
nicholas cage况下，优化各个杆件的尺寸，使结构在满足约束条件的
同时达到结构总质量最轻㊁设计合理性最佳㊁工程成本
质量最轻，即为结构优化[1-2]㊂结构优化设计变量多，采用传统的计算方法解决这些问题面临着计算复杂度高㊁计算时间长等问题，对具有启发式特征的计算智能方法的研究越来越活跃㊂而过去十年里，一系列智能算法正在兴起，如遗传算法(genetic algorithm ,GA )㊁粒子群优化算法(particle swarm optimization ,PSO )㊁蚁群优化(ant colony optimization ,ACO )㊁模拟退火(simulated an⁃nealing ,SA )㊁和声搜索(harmony arch ,HS )和萤火虫第30卷 第5期2020年5月 计算机技术与发展COMPUTER TECHNOLOGY AND DEVELOPMENT
Vol.30 No.5May 2020tua
