Publication Detail

Evaluating Sustainable Vehicle Technologies for Freight Transportation Using Spherical Fuzzy AHP and TOPSIS


Journal Article

Sustainable Freight Research Program

Suggested Citation:
Jaller, Miguel and Irem Otay (2020) Evaluating Sustainable Vehicle Technologies for Freight Transportation Using Spherical Fuzzy AHP and TOPSIS. Institute of Transportation Studies, University of California, Davis, Journal Article UCD-ITS-RP-20-32

Freight transportation is vital for the economy and everyday life. It brings the goods and services needed for industrial and manufacturing processes, as well as those to be consumed by the population. However, the vehicles (mostly diesel trucks) used are responsible for a disproportionate amount of environmental externalities. Therefore, it is imperative to manage transport demand, and foster the use of cleaner vehicles, fuels and technologies. The most common alternatives include compressed (renewable) natural gas (CNG/RNG), hybrid electric (HE), battery electric (BE) and fuel-cell hydrogen (H2) vehicles. However, the technical and operational characteristics, market readiness, and other factors related to these technologies can be very different. Therefore, the most appropriate option for different uses (e.g., last mile, long-haul distribution) and users’ preferences is not necessarily clear. Consequently, this paper proposes Analytic Hierarchy Process (AHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) based on Spherical fuzzy sets to evaluate the sustainable vehicle technology alternatives over multiple criteria for freight transportation. Spherical fuzzy sets have been receiving increasing attention because of their ability to better consider uncertainty by defining membership functions on a Spherical surface and covering a larger domain. Specifically, the authors evaluate the alternatives using five criteria: Financial; Business & market-related; Environmental & legal; Maintenance & repair availability; and Safety & vehicle performance factors, and 21 sub-criteria. Moreover, the authors also performed sensitivity analysis.
Key words: Freight transportation, Vehicle and fuel pathways, Spherical Fuzzy AHP, Spherical fuzzy TOPSIS, Spherical fuzzy sets, Multi-criteria decision making