A Large-scale Freight Train Diagram Optimization Heuristic Algorithm Based on Lagrangian Relaxation

被引：0
|
作者：
Jiang F. [1 ,2 ]
Ni S. [1 ,2 ]
机构：
[1] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu
[2] National Railway Train Diagram Research and Training Center, Southwest Jiaotong University, Chengdu
来源：
Tiedao Xuebao/Journal of the China Railway Society | 2020年 / 42卷 / 03期
关键词：
Freight train diagram; Heuristic algorithm; Inter programming; Lagrangian relaxation; Train path drawing strategy;
D O I：
10.3969/j.issn.1001-8360.2020.03.003
中图分类号：
学科分类号：
摘要：
Considering the problem of large scale and difficulty to achieve a precise solution in the optimization of freight train operation diagram, this paper used a time-space graph to describe the train path drawing as a routing solving problem, and transformed various constraints into the selection violation of the node of the time-space graph, to establish an integer programming model. The nature of the problem is to solve the possible conflicts among train paths, to relax the model in a Lagrangian way, and to represent the possible conflicts among train paths as the node penalty. A heuristic algorithm was used to obtain feasible solution and update the Lagrangian multiplier to optimize iteratively. Based on the verification study of the Beijing West-Fuyang section of Beijing West-Jiulong railway, an optimization experiment was conducted on 439 freight train paths out of all 711 train paths in the section. The results show that, under the precondition of satisfying the demand of arranging all the train paths, the average travel speed has increased from 39.28 km/h to 41.81-43.72 km/h. The algorithm proposed is effective in solving large-scale freight train diagram optimization. © 2020, Department of Journal of the China Railway Society. All right reserved.
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页码：21 / 31
页数：10
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