Multi-Criteria Selection of Electric Delivery Vehicles Using Fuzzy–Rough Methods

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dc.citation.spage15541
dc.citation.volume15
dc.contributor.authorWang, Ning
dc.contributor.authorXu, Yong
dc.contributor.authorPuška, Adis
dc.contributor.authorStević, Željko
dc.contributor.authorAlrasheedi, Adel Fahad
dc.date.accessioned2024-11-19T11:11:03Z
dc.date.available2024-11-19T11:11:03Z
dc.date.issued2023
dc.description.abstractUrban logistics implementation causes environmental pollution; therefore, it is necessary to consider the impact on the environment when carrying out such logistics. Electric vehicles are alternative vehicles that reduce the impact on the environment. For this reason, this study investigated which electric vehicle has the best indicators for urban logistics. An innovative approach when selecting such vehicles is the application of a fuzzy–rough method based on expert decision making, whereby the decision-making process is adapted to the decision makers. In this case, two methods of multi-criteria decision making (MCDM) were used: SWARA (stepwise weight assessment ratio analysis) and MARCOS (measurement alternatives and ranking according to compromise solution). By applying the fuzzy–rough approach, uncertainty is included when making a decision, and it is possible to use linguistic values. The results obtained by the fuzzy–rough SWARA method showed that the range and price of electric vehicles have the greatest influence on the selection of an electric delivery vehicle. The results of applying the fuzzy–rough MARCOS method indicated that the Kangoo E-Tech Electric vehicle has the best characteristics according to experts’ estimates. These results were confirmed by validation and the application of sensitivity analysis. In urban logistics, the selection of an electric delivery vehicle helps to reduce the impact on the environment. By applying the fuzzy–rough approach, the decision-making problem is adjusted to the preferences of the decision makers who play a major role in purchasing a vehicle.
dc.identifier.doi10.3390/su152115541
dc.identifier.urihttps://vaseljena.ues.rs.ba/handle/123456789/1307
dc.language.isoen
dc.publisherMDPI
dc.sourceSustainability
dc.subjectselection of electric delivery vehicles; urban logistics; sustainability; fuzzy–rough numbers
dc.titleMulti-Criteria Selection of Electric Delivery Vehicles Using Fuzzy–Rough Methods
dc.typeArticle
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Саобраћајни факултет [Научни радови] / Faculty of Transport and Traffic Engineering [Scientific papers]