Subscribe Now Subscribe Today
Science Alert
Curve Top
Journal of Applied Sciences
  Year: 2013 | Volume: 13 | Issue: 9 | Page No.: 1544-1550
DOI: 10.3923/jas.2013.1544.1550
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Models and Algorithms of Locomotive Layout Optimization in Regional Heavy Haul Rail Network

Junhua Chen, Qi Liu, Jian Yu and Yajing Zheng

The locomotive layout which is extremely hard to modify after the construction, has direct impact on the daily transport efficiency and economic benefit of the railway transportation company. Therefore, it should be optimized once the rail network pattern is changed. The regional heavy haul rail network is a half open transportation system. Constant changes exist in the long period. As a result, the modification of locomotive system productivity layout is hard to be timely and effective. This problem differs from the normal logistic location problem and has complex influencing factors. Existing literatures mainly focus on the qualitative solutions which cannot precisely show the advantages and disadvantages of the alternative solutions and lack enough persuasion. The two key points of this problem is (1) Reasonable and reliable index system and (2) Feasible and practical models and algorithms. The numerical example takes the regional heavy haul rail network of Shenhua Group. The evaluation index system that can reflect the random factors is built. Then the model and the corresponding algorithm that can comprehensively evaluate the alternative solutions are proposed, through the combination of the fuzzy analytical hierarchy process and gray correlation analysis method. The locomotive layout optimization results conform to the reality well and promote the locomotive operational efficiency which will have positive impact on the development of the long-locomotive-line operation mode.
PDF References Citation Report Citation
How to cite this article:

Junhua Chen, Qi Liu, Jian Yu and Yajing Zheng, 2013. Models and Algorithms of Locomotive Layout Optimization in Regional Heavy Haul Rail Network. Journal of Applied Sciences, 13: 1544-1550.

DOI: 10.3923/jas.2013.1544.1550






Curve Bottom