Vehicle routing software selection for last mile delivery companies using Fermatean fuzzy-based model

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dc.contributor.authorKara, Karahan
dc.contributor.authorYalçın, Galip Cihan
dc.contributor.authorSimic, Vladimir
dc.contributor.authorGürol, Pınar
dc.contributor.authorPamucar, Dragan
dc.date.accessioned2024-11-27T07:41:41Z
dc.date.available2024-11-27T07:41:41Z
dc.date.issued2024
dc.departmentAÇÜ, Hopa Meslek Yüksekokulu, Yönetim ve Organizasyon Bölümüen_US
dc.description.abstractVehicle routing software (VRS) is utilized by last mile delivery (LMD) companies for route optimization. The problem of VRS selection is of paramount importance for LMD companies. In this research, a VRS selection model tailored to LMD companies is developed and proposed. This model is based on Fermatean fuzzy sets (FFS). The FFS-preference selection index (PSI) method is proposed for weighting the criteria. The FFS-alternative ranking order method accounting for two-step normalization (AROMAN) method is defined for ranking the VRS alternatives. This hybrid approach, developed as FFS-PSI-AROMAN, incorporates the FFYWA operator based on Yager t-norm and t-conorm operations as the aggregation operator to enhance the strength of aggregation operations. Additionally, an algorithm has been developed for the model. The developed model is applied through a real-life case study conducted in an LMD company operating in Turkey. An expert group is formed, criteria are defined, alternative VRS options are identified, and the proposed algorithm is employed to make the optimal VRS selection. Sensitivity analysis scenarios are created, and robustness tests are conducted to evaluate the model's reliability. Comprehensive implications for both the research and managerial insights are provided, along with recommendations for future research endeavors.
dc.identifier.doi10.1016/j.engappai.2023.107813
dc.identifier.issn0952-1976
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.engappai.2023.107813
dc.identifier.urihttps://hdl.handle.net/11494/5031
dc.identifier.volume131en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofEngineering Applications of Artificial Intelligence
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectAlternative Ranking Order Method Accounting For Two-Step Normalizationen_US
dc.subjectFermatean Fuzzy Setsen_US
dc.subjectLast Mile Deliveryen_US
dc.subjectPreference Selection Indexen_US
dc.subjectVehicle Routing Software Selectionen_US
dc.titleVehicle routing software selection for last mile delivery companies using Fermatean fuzzy-based modelen_US
dc.typeArticle

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