Kent İçi Toplu Taşıma Sistemlerini Sıralayan Yeni Bir Bulanık Mantık Tabanlı Yöntem

Özet (abstract)

The selection of the right public transport system is crucial in shaping environmental accessibility, economic prospects, and quality of life in urban cities. It is considered a multi-criteria group decision-making problem because of the presence of multiple criteria, experts, and uncertain information. Accordingly, this study aims to propose a decision support model on intuitionistic fuzzy sets (IFSs) for identifying and evaluating the public transit systems. The proposed method evaluates the significance degrees of involved experts using the intuitionistic fuzzy coefficient of variation model. Next, the proposed framework presents the modified criteria importance through intercriteria correlation (CRITIC)-relative closeness coefficient (RCC)-based combined objective-subjective criteria weighting model considering a new divergence measure on IFSs. The proposed divergence measure is used to effectively quantify the discrimination between intuitionistic fuzzy information, which improves the reliability of obtained criteria weights. This framework further presents an improved compromise ranking from alternative solutions (CORASO) approach for ranking the options under an IFSs context. To reveal the applicability of the developed framework, it is implemented in a case study of urban public transportation systems’ assessment of Ankara, Turkiye. The results indicate that the option "Commuter trains" is the most suitable urban public transport system among the considered alternatives in Ankara, Turkiye. At last, this study conducts sensitivity and comparative analysis, confirming the steadiness and robustness of the proposed framework. The findings of this work help urban planners to select suitable public transport systems for metropolitan cities.

Yazarların özeti; kaynağından alınmıştır. Engineering Applications of Artificial Intelligence, 2026 · DOI ↗