A novel model based on the fuzzy Grey Relational Analysis (F-GRA) approach for selecting the appropriate high-speed train set

dc.authoridPRAKASH, CHANDRA/0000-0002-0619-215X
dc.contributor.authorGarg, Chandra Prakash
dc.contributor.authorGorcun, Omer F.
dc.contributor.authorKucukonder, Hande
dc.date.accessioned2023-10-19T15:12:36Z
dc.date.available2023-10-19T15:12:36Z
dc.date.issued2023
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, Turkiyeen_US
dc.description.abstractThe 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.citation1
dc.identifier.doi10.1007/s00500-023-08284-9en_US
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.scopus2-s2.0-85159408231en_US
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1007/s00500-023-08284-9
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5488
dc.identifier.wosWOS:000988438400020en_US
dc.identifier.wosqualityQ2
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRailEn_Us
dc.subjectCostEn_Us
dc.subjectEfficiencyEn_Us
dc.subjectTransportEn_Us
dc.subjectLocationEn_Us
dc.subjectAhpEn_Us
dc.subjectAirEn_Us
dc.subjectRail
dc.subjectCost
dc.subjectEfficiency
dc.subjectTransport
dc.subjectLocation
dc.subjectHigh-speed trainsen_US
dc.subjectAhp
dc.subjectFuzzy GRAen_US
dc.subjectAir
dc.subjectFuzzy numbersen_US
dc.titleA novel model based on the fuzzy Grey Relational Analysis (F-GRA) approach for selecting the appropriate high-speed train seten_US
dc.typeArticleen_US
dspace.entity.typePublication

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