Convergence and calculation speed of genetic algorithm in structural engineering optimization

被引：0
|
作者：
Zhu, Yunhua [1 ]
Cai, Xiao [1 ]
机构：
[1] College of Business Administration, Huaqiao University, Quanzhou, Fujian, China
来源：
Metallurgical and Mining Industry | 2015年 / 7卷 / 08期
关键词：
Genetic algorithms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In view of the existing genetic algorithm in structural engineering optimization has poor convergence, computational speed is slow, a optimization scheme of genetic algorithm is proposed in this paper based on the crossover operator and fitness function. The first use of the hybrid mechanism of the single point crossover operator of genetic algorithm is improved, in order to improve the searching space, and then the small to adapt to the optimization of the habitat mechanism of sharing function convergence. The simulation results show that, the crossover operator and fitness function based genetic algorithm optimization in structural engineering optimization has better, faster and better stability.
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页码：259 / 263
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