基于改进遗传算法的临时转播塔结构优化设计方法

doi:10.3785/j.issn.1008-973X.2025.03.004

浙江大学学报(工学版)

2025, Vol. 59

Issue (3): 469-479 DOI: 10.3785/j.issn.1008-973X.2025.03.004

交通工程、土木工程

基于改进遗传算法的临时转播塔结构优化设计方法

邢国华(

),陆勇健,苗鹏勇*(

),陈思锦

长安大学建筑工程学院，陕西西安 710061

Optimal design method of temporary broadcasting tower structure based on improved genetic algorithm

Guohua XING(

),Yongjian LU,Pengyong MIAO*(

),Sijin CHEN

School of Civil Engineering, Chang’an University, Xi’an 710061, China

全文: PDF(1957 KB) HTML

摘要：

针对临时转播塔结构用钢质量较大且设计过程精细化程度低的问题，提出模块化临时转播塔结构及其优化设计方法. 所提设计方法将参数化建模与综合优化相结合，利用ANSYS建立结构参数化有限元模型，考虑结构设计参数在寻优过程中引起的风荷载变化；采用初始替换、差异化、自适应遗传等5种策略提升浮点数编码遗传算法(FGA)的搜索能力和收敛性能，提出改进浮点数编码遗传算法(IFGA)，综合优化临时转播塔结构的尺寸、形状和杆件布置形式，实现结构轻量化设计. 工程实例的应用表明，模块化临时转播塔结构的力学性能良好；在结构轻量化方面，IFGA算法相较于FGA算法优化结果在用钢质量上降低18.9%，相较于学校算法、鲸鱼算法及改进灰狼算法具有更高的计算效率和寻优能力；建议的优化设计方法高效、可靠，能在确保结构安全的前提下较初始方案在用钢质量上降低33.2%.

关键词： 结构优化; 遗传算法; 有限元; 轻量化设计; 临时转播塔

Abstract:

A modular temporary broadcasting tower structure and its optimal design method were proposed to address the issues of excessive steel usage and low design refinement in temporary broadcast tower structures. The optimal design method combined parametric modeling and comprehensive optimization. Parametric finite element model was achieved using ANSYS to consider wind load fluctuations caused by structural design parameters during the optimization process. Five strategies including initial replacement, differentiation and adaptive genetics were used to enhance the search capability and convergence performance of the float-encoded genetic algorithm (FGA), leading to the proposal of an improved float-encoded genetic algorithm (IFGA). The IFGA was then utilized to comprehensively optimize the cross-section, shape, and members’ arrangement for the temporary broadcasting tower structure to achieve a lightweight plan. Validating in practical engineering revealed that the modular temporary broadcasting tower structure had excellent mechanical performance. In terms of structural lightweighting, the IFGA reduced the quality of steel used by 18.9% compared with the FGA, and it surpassed the school algorithm, whale algorithm and improved grey wolf algorithm in computational efficiency and optimization prowess. As a result, the proposed optimal design method was efficient and reliable, could save 33.2% of the quality of steel used compared with the original plan while ensuring structural safety.

Key words: structural optimization genetic algorithm finite element lightweight design temporary broadcasting tower

收稿日期: 2023-12-26 出版日期: 2025-03-10

CLC:

TU 311.41

基金资助: 陕西省重点研发计划“两链”融合企业（院所）联合重点专项(2022LL-JB-13).

通讯作者: 苗鹏勇 E-mail: ghxing@chd.edu.cn;p.y.miao@outlook.com

作者简介: 邢国华（1983—），男，教授，从事结构设计与防灾减灾研究. orcid.org/0000-0003-3725-5704. E-mail：ghxing@chd.edu.cn

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引用本文:

邢国华,陆勇健,苗鹏勇,陈思锦. 基于改进遗传算法的临时转播塔结构优化设计方法[J]. 浙江大学学报(工学版), 2025, 59(3): 469-479.

Guohua XING,Yongjian LU,Pengyong MIAO,Sijin CHEN. Optimal design method of temporary broadcasting tower structure based on improved genetic algorithm. Journal of ZheJiang University (Engineering Science), 2025, 59(3): 469-479.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2025.03.004 或 https://www.zjujournals.com/eng/CN/Y2025/V59/I3/469

图 1 塔架标准节

图 2 模块化临时转播塔结构

表 1 临时转播塔结构设计变量

表 2 有限元模型计算结果对比

图 3 斜杆布置形式

图 4 适应度计算流程

图 5 种群初始化流程

图 6 种群差异化流程

图 7 IFGA算法的计算流程

图 8 优化设计系统的部分交互界面

图 9 改进前后遗传算法的初始种群

表 3 不同策略遗传算法的优化结果与计算成本

图 10 不同策略遗传算法的进化历程

表 4 不同算法的优化结果与计算成本

图 11 不同算法的进化历程

图 12 结构总质量的进化历程

表 5 优化前后设计方案的质量变化

图 13 优化前后临时转播塔的标准节

图 14 部分约束变量的进化历程

图 15 优化前后杆件的等效应力

表 6 优化前后结构设计变量的对比

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