An Integrated Intuitionistic Fuzzy Closeness Coefficient-Based OCRA Method for Sustainable Urban Transportation Options Selection

Transportation systems play a key role in urban development by providing access for people to markets and education, employment, health care, recreation, other services. However, uncontrolled population fast growth of vehicle mobility inevitably lead unsustainable transportation terms economic, technical, social, geographical aspects sustainability. Thus, there is need select suitable sustainable (SUT) alternatives, which can contributed the technological advancement city changes societal necessities, mitigating climate change impact from transport transforming living habits, context high growth. Therefore, this paper aims introduce an integrated multi-attribute decision analysis (MADA) framework assessing ranking options under intuitionistic fuzzy sets (IFSs) context. In regard, firstly IF-distance measures their properties are developed obtain criteria weight. Second, IF-relative closeness coefficient-based model presented find weights. Third, operational competitiveness rating (OCRA) introduced with IF-score function-RS-based experts’ weighing relative weight determination IFSs environment. To exemplify utility effectiveness OCRA methodology, case study different SUT bus perspective. A comparison models made prove superiority solidity obtained outcome. Moreover, comparative outperforms extant MADA models, as it provide more sound outcomes than others, thus efficient elucidate uncertain information handling practical problems. study, we analyze determine most considering environmental, social dimensions sustainability also make significant contribution current scientific knowledge novel support system uncertainty