Leading the green charge: A novel type-2 fuzzy VIKOR method applied to eco-conscious freight transport
Year: 2025
Type: article
Abstract: Imprecise and ambiguous information is critical in multi-criteria group decision-making (MCGDM) problems. Quantification of such information is essential in determining the best alternative. In this study, an interval type-2 fuzzy set (IT2FS) possibility-based Vlsekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) approach is developed to address MCGDM problems. The possibilities of IT2FSs are employed to establish a new decision matrix containing crisp information, which decreases the computational complexities involved with processing IT2FSs. With the use of the new decision matrix, decision-makers (DMs) may now assess alternatives in pairs to determine which alternatives have benefits over the others. Due to the adoption of possibilities of IT2FSs, the proposed approach works efficiently even in cases where the differences between alternatives are minor. Since road freight transport emissions represent a very significant contributor to transportation-related greenhouse gas emissions , there is an urgent need to seek sustainable solutions in this area. Thus, the model is applied to the road freight transport to rank different fuel alternatives . The proposed possibility-based VIKOR method provides a robust framework for evaluating renewable fuel alternatives by considering sustainability benefits and market barriers, while overcoming several key limitations of traditional MCDM methods. It is recommended that this approach be utilized in real-world decision-making for sustainable freight transport planning. Future research could explore its integration with dynamic data sources for more adaptive and real-time decision support.
Source: Expert Systems with Applications
Institutions: RWTH Aachen University, Forschungszentrum Jülich
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
OpenAlex ID: W4410197584
