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Mathematical Problems in Engineering
Volume 2015, Article ID 404926, 25 pages
Research Article

Service Station Evaluation Problem in Catering Service of High-Speed Railway: A Fuzzy QFD Approach Based on Evidence Theory

Xin Wu,1,2 Lei Nie,1,2 and Meng Xu2

1School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China

Received 10 April 2015; Revised 17 June 2015; Accepted 24 June 2015

Academic Editor: Zdeněk Kala

Copyright © 2015 Xin Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Catering Service of High-Speed Railway (CSHR) starts at suppliers, includes distribution centers and service stations in cities, and ends at cabinets in high-speed trains. In Distribution System Design (DSD) Problem for CSHR, it is critical to evaluate the alternatives of service stations, which is termed as Service Station Evaluation Problem in Catering Service of High-speed Railway (SSEP-CSHR). As a preparation work for DSD, SSEP-CSHR needs to be solved without detailed information and being accompanied with uncertainty. Fuzzy Quality Function Deployment (F-QFD) has been given in the literatures to deal with vagueness in Facility Location Evaluation (FLE). However, SSEP-CSHR that includes identifying and evaluating stations requires not only dealing with the vague nature of assessments but also confirming them. Based on evidence theory, this paper introduces the framework to give the truth of proposition “ is .” Then it is incorporated into a two-phase F-QFD with an approximate reasoning to enable the truth of the decisions to be measured. A case study that refers to 85 alternative stations on Chinese high-speed railway will be carried out to verify the proposed method. Analysis shows that the proposed evaluation method enhances scientific credibility of FLE and allows decision makers to express how much is known.