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.citation | 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.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 |
dspace.entity.type | Publication |
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