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基于蚁群算法的桁架结构布局离散变量优化方法
引用本文:张卓群,李宏男.基于蚁群算法的桁架结构布局离散变量优化方法[J].计算力学学报,2013,30(3):336-342.
作者姓名:张卓群  李宏男
作者单位:大连理工大学建设工程学部,大连,116024
基金项目:国家自然科学基金委创新研究群体基金(51121005)资助项目.
摘    要:提出的布局优化方法是将桁架结构的截面变量、拓扑变量及形状变量统一为离散变量.将离散变量转化为适应于蚁群算法求解TSP问题的离散变量,应用MATLAB语言编写求解桁架结构布局优化程序,最终实现对问题的分析与求解.通过对几个经典的平面、空间桁架结构布局优化算例的验算表明:本文设计的基于蚁群算法的桁架结构布局离散变量优化方法较单独处理截面优化、拓扑优化及形状优化问题具有更大的效益,相对于其他布局优化方法也展现出更好的优化效果.“基于蚁群算法的桁架结构布局离散变量优化方法”在程序设计、求解速度、求解空间及其方法通用性等方面都表现出良好的性能,并且简单、实用,适应于实际工程应用.

关 键 词:布局优化  蚁群算法  离散变量  桁架结构  TSP问题
收稿时间:2011/10/21 0:00:00
修稿时间:5/6/2012 12:00:00 AM

The method of truss structure layout discrete variable optimization based on Ant Colony Optimization
ZHANG Zhuo-qun and LI Hong-nan.The method of truss structure layout discrete variable optimization based on Ant Colony Optimization[J].Chinese Journal of Computational Mechanics,2013,30(3):336-342.
Authors:ZHANG Zhuo-qun and LI Hong-nan
Institution:Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China;Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China
Abstract:The purpose of the truss structure layout optimization method is that cross-section,topology and shape variables unified discrete variables.The discrete variables have been transformed into the TSP problem variables to adapt the ant colony optimization algorithm.The MATLAB procedure of Truss Structure layout optimization has been developed to solve this problem.By checking some classical plane and space truss structure of the layout optimization examples by the MATLAB simplified procedure,in discrete system,it is considered that the result of layout optimization has much greater efficiency,compared to separate cross-section optimization,topology optimization and shape optimization,and is better than the other layout optimization algorithms.Although this paper presented that the method of truss structure layout optimization based on ant colony optimization is preliminary research in truss layout optimization method,the idea has shown good performance in program design,solution speed,solution space,and generality and so on.This algorithm is very simple,practical and suitable for engineering.
Keywords:layout optimization  Ant Colony Optimization (ACO)  discrete variable  truss structure  Traveling Salesman Problem (TSP)
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