基于改进蚁群算法的连续型桁架结构优化设计研究

龚雨兵

doi:10.13433/j.cnki.1003-8728.2014.0605

基于改进蚁群算法的连续型桁架结构优化设计研究

doi: 10.13433/j.cnki.1003-8728.2014.0605

龚雨兵

1.
桂林电子科技大学,机电工程学院桂林 541004

详细信息

作者简介:
龚雨兵(1978-)，副教授，博士，研究方向为结构优化算法，gybcome@guet.eud.cn

计量
- 文章访问数: 125
- HTML全文浏览量: 23
- PDF下载量: 6
- 被引次数: 0
出版历程
- 收稿日期: 2012-12-04
- 刊出日期: 2015-06-10

Optimization Design of Continuous Truss Structures Based on an Improved Ant Colony Optimization Algorithm

Gong Yubing

1.
Electromechanical Engineering College,Guilin University of Electronic Technology,Guilin 541004

摘要

摘要: 采用二进制编码方法对连续域设计变量进行离散化处理,对每代蚁群进行交叉、变异和复制等操作。对蚁群算法路径信息素更新方法应用了新的改进方式。应用这种二进制改进蚁群算法,对典型的10杆平面桁架及72杆空间桁架结构进行了结构分析与优化。采用改进方法的10杆最优设计方案比目前最优结果,略高0.18%;72杆最优设计方案优于目前最优设计结果,相对优化了2.8%。
- 优化 /
- 结构分析 /
- 蚁群算法 /
- 连续变量
Abstract: The Ant Colony Optimization (ACO) algorithm with an improved pheromone updating rule wasintroduced in this paper, in which the binary coding was used to transfer the continuous variables to discretevariables. The improved ACO algorithm was applied to analysis and optimization of two classical truss structures,namely the ten-bar plane truss and the seventy two-bar space truss. The comparisons between improved ACO andother algorithms in the previous literatures show that for the ten-bar truss optimization, the optimum solutionobtained by improved ACO algorithm is closer to the optimum value than other algorithms, where the relativedeviation is about 0. 18%; for the seventy two-bar space truss optimization, the optimum design is better than thoseof other algorithms, where the relative deviation is about 2. 8%.
- ant colony algorithm /
- binary codes /
- continuous variables /
- design

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参考文献(20)

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