A Novel Model Based on the Fuzzy Grey Relational Analysis (f-Gra) Approach for Selecting the Appropriate High-Speed Train Set

dc.authorid PRAKASH, CHANDRA/0000-0002-0619-215X
dc.contributor.author Garg, Chandra Prakash
dc.contributor.author Gorcun, Omer F.
dc.contributor.author Kucukonder, Hande
dc.date.accessioned 2023-10-19T15:12:36Z
dc.date.available 2023-10-19T15:12:36Z
dc.date.issued 2023
dc.department-temp [Garg, Chandra Prakash] Indian Inst Management Rohtak, Dept Operat Management & Quantitat Tech, Rohtak 124010, Haryana, India; [Gorcun, Omer F.] Kadir Has Univ, Fac Econ Adm & Social Sci, Dept Business Adm, Cibali Ave,Kadir Has St Fatih, TR-34083 Istanbul, Turkiye; [Kucukonder, Hande] Bartin Univ, Fac Econ & Adm, Dept Numer Methods, Bartin, Turkiye en_US
dc.description.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. en_US
dc.identifier.citationcount 1
dc.identifier.doi 10.1007/s00500-023-08284-9 en_US
dc.identifier.issn 1432-7643
dc.identifier.issn 1433-7479
dc.identifier.scopus 2-s2.0-85159408231 en_US
dc.identifier.scopusquality Q2
dc.identifier.uri https://doi.org/10.1007/s00500-023-08284-9
dc.identifier.uri https://hdl.handle.net/20.500.12469/5488
dc.identifier.wos WOS:000988438400020 en_US
dc.identifier.wosquality Q2
dc.khas 20231019-WoS en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.relation.ispartof Soft Computing en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 4
dc.subject Rail En_Us
dc.subject Cost En_Us
dc.subject Efficiency En_Us
dc.subject Transport En_Us
dc.subject Location En_Us
dc.subject Ahp En_Us
dc.subject Air En_Us
dc.subject Rail
dc.subject Cost
dc.subject Efficiency
dc.subject Transport
dc.subject Location
dc.subject High-speed trains en_US
dc.subject Ahp
dc.subject Fuzzy GRA en_US
dc.subject Air
dc.subject Fuzzy numbers en_US
dc.title A Novel Model Based on the Fuzzy Grey Relational Analysis (f-Gra) Approach for Selecting the Appropriate High-Speed Train Set en_US
dc.type Article en_US
dc.wos.citedbyCount 4
dspace.entity.type Publication

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