A Novel Model Based on the Fuzzy Grey Relational Analysis (f-Gra) Approach for Selecting the Appropriate High-Speed Train Set
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Date
2023
Authors
Garg, Chandra Prakash
Gorcun, Omer F.
Kucukonder, Hande
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic.
Description
ORCID
Keywords
Rail, Cost, Efficiency, Transport, Location, Ahp, Air, Rail, Cost, Efficiency, Transport, Location, High-speed trains, Ahp, Fuzzy GRA, Air, Fuzzy numbers, Rail, Cost, Ahp, Fuzzy GRA, Location, Air, Transport, Efficiency, Fuzzy numbers, High-speed trains, Fuzzy Gra, Fuzzy Numbers, High-Speed Trains
Fields of Science
05 social sciences, 02 engineering and technology, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering
Citation
WoS Q
Q3
Scopus Q
Q1

OpenCitations Citation Count
2
Source
Soft Computing
Volume
27
Issue
24
Start Page
19247
End Page
19264
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