Home           Contact us           FAQs           
 
   Journal Page   |   Aims & Scope   |   Author Guideline   |   Editorial Board   |   Search
    Abstract
2013 (Vol. 6, Issue: 05)
Article Information:

Location Selection of Chinese Modern Railway Logistics Center Based on DEA-Bi-level Programming Model

Fenling Feng, Feiran Li and Qingya Zhang
Corresponding Author:  Fen-ling FENG 

Key words:  Bi-level programming, DEA, location problem, modern railway logistics center, , ,
Vol. 6 , (05): 812-818
Submitted Accepted Published
September 17, 2012 November 13, 2012 June 25, 2013
Abstract:

Properly planning the modern railway logistics center is a necessary step for the railway logistics operation, which can effectively improve the railway freight service for a seamless connection between the internal and external logistic nodes. The study, from the medium level and depending on the existing railway freight stations with the railway logistics node city, focuses on the site-selection of modern railway logistics center to realize organic combination between newly built railway logistics center and existing resources. Considering the special features of modern railway logistics center, the study makes pre-selection of the existing freight stations with the DEA assessment model to get the alternative plan. And further builds a Bi-level plan model with the gross construction costs and total client expenses minimized. Finally, the example shows that the hybrid optimization algorithm combined with GA, TA, SA can solve the Bi-level programming which is a NP-hard problem and get the railway logistics center number and distribution. The result proves that our method has profound realistic significance to the development of China railway logistics.
Abstract PDF HTML
  Cite this Reference:
Fenling Feng, Feiran Li and Qingya Zhang, 2013. Location Selection of Chinese Modern Railway Logistics Center Based on DEA-Bi-level Programming Model.  Research Journal of Applied Sciences, Engineering and Technology, 6(05): 812-818.
    Advertise with us
 
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Current Information
   Sales & Services
   Contact Information
  Executive Managing Editor
  Email: admin@maxwellsci.com
  Publishing Editor
  Email: support@maxwellsci.com
  Account Manager
  Email: faisalm@maxwellsci.com
  Journal Editor
  Email: admin@maxwellsci.com
  Press Department
  Email: press@maxwellsci.com
Home  |  Contact us  |  About us  |  Privacy Policy
Copyright © 2009. MAXWELL Science Publication, a division of MAXWELLl Scientific Organization. All rights reserved