Intelligent railway alignment optimization based on stepwise encoding genetic algorithm

被引：0
作者：
Li, Wei [1 ,2 ]
Pu, Hao [1 ,2 ]
Zhao, Haifeng [1 ,2 ]
Hu, Jianping [3 ]
Meng, Cunxi [4 ]
机构：
[1] School of Civil Engineering, Central South University
[2] National Engineering Laboratory for High Speed Railway Construction
[3] China Railway Eryuan Engineering Group Co. Ltd.
[4] China Railway First Survey and Design Institute Group Ltd.
来源：
Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University | 2013年 / 48卷 / 05期
关键词：
Genetic algorithm; Horizontal-vertical alignment simultaneous optimization; Intelligent alignment; Railway alignment;
D O I：
10.3969/j.issn.0258-2724.2013.05.008
中图分类号：
学科分类号：
摘要：
In order to achieve the optimization of railway 3D alignments, an optimization model was built, in which comprehensive factors including construction, operation, environment, and constraints were embedded. Different distributions for horizontal and vertical control points were presented. A genetic series that consists of offsets of intersection points, the radii of the circular curve, and the elevations of grade change points was designed. Then a stepwise horizontal-vertical-integral genetic encoding method was put forward, and the genetic operators for crossover and mutation were also designed to achieve the optimization of railway alignments. The results of application examples indicate that this method can overcome the shortcoming of the overlapping of horizontal curves and vertical curves, and yield a group of alignments with low comprehensive costs and meanwhile conforming to railway constraints. The optimal alignment obtained by this optimization method can reduce the overall comprehensive cost by 6.5% than the alignment obtained by human work.
引用
收藏
页码：831 / 838
页数：7
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