Research Article | OPEN ACCESS
The Analysis of Shunting Locomotives' Operating Efficiency Based on Gray-DEA
Yunli Zhang, Dingyou Lei, Xiamiao Li and Yanbing Fu
Department of Traffic and Transportation Engineering, Central South University,
Changsha 410075, China
Research Journal of Applied Sciences, Engineering and Technology 2013 5:1720-1725
Received: July 27, 2012 | Accepted: September 03, 2012 | Published: February 11, 2013
Abstract
In order to explore the configuration of the railway freight shunting locomotives, improve the efficiency of locomotive operation; a DEA cross evaluating method based on grey incidence analysis is presented in this paper. This method is based on collecting underlying data of factors that influence the shunting operation efficiency in train service depot, which utilizes grey incidence analysis to establish corresponding evaluation indicators system. Furthermore, the method as well adopts DEA and DEA cross efficiency model to analyze, evaluate and estimate the efficiency of shunting locomotives operation in train service depots. A sorting result of the efficiency of shunting locomotives operation in each train service depot has been acquired with help of programming using MATLAB 7.0. What the result indicates is that the DEA cross efficiency evaluating model based on grey incidence analysis can reflect the actual state of the efficiency of shunting locomotives operation in each train service depot. Eventually, based on a projection analysis of non-DEA's three decision-making units, key factors that influence the efficiency of shunting locomotives operation are identified, which can provide decision support for further improvement of the configuration and operation in train service depots.
Keywords:
Cross evaluation, DEA, efficiency of shunting locomotives operation, grey incidence analysis,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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