Kara, KarahanYalçın, Galip CihanSimic, VladimirGürol, PınarPamucar, Dragan2024-01-232024-01-232024https://hdl.handle.net/11467/7120https://doi.org/10.1016/j.engappai.2023.107813Vehicle 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.eninfo:eu-repo/semantics/embargoedAccessLast mile delivery, Vehicle routing software selection, Fermatean fuzzy sets, Preference selection index, Alternative ranking order method accounting for two-step normalizationVehicle routing software selection for last mile delivery companies using Fermatean fuzzy-based modelArticle131N/AWOS:001164220000001N/A2-s2.0-8518228351210.1016/j.engappai.2023.107813