A genetic algorithm for obtaining the optimal locomotive working diagram with double-shoulder circuit locomotive routing by the mode of unfixed traction

被引：0

作者：

He, Fengdao ^{[1
]}

He, Dongyun ^{[2
]}

机构：

[1] School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China

[2] Business School, Sichuan University, Chengdu 610064, China

来源：

Zhongguo Tiedao Kexue/China Railway Science | 2007年 / 28卷 / 01期

关键词：

Combinatorial optimization - Genetic algorithms - Knowledge based systems - Mathematical models - Mathematical operators - Shoulders (road) - Transportation routes;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Locomotive working diagram is a multi-constraint combinatorial optimization problem. A mathematical model is established for double-shoulder circuit locomotive routing by the mode of unfixed traction. The objective is to minimize the total time for locomotives staying in districts, and the optimized schedule is obtained with a genetic algorithm. The abilities of local search, convergence and optimization are raised with the knowledge-based mutation operator and the crossing probability, mutating probability self-adjusted by the fitness of the individual. The proposed method was tested over an actual problem of train working diagram. The results show that compared with actual locomotive working diagram, the total time of locomotives staying in districts and the required number of locomotives is reduced by about 21% and 8.6% respectively.

引用

页码：118 / 122