A Cooperative Neutrosophic Sets with Dual Rough Set and Entropy Enhanced Multi-Similarity Measures Based Decision Making for Sustainable Transportation

Sustainable transportation helps address environmental, social and urban mobility challenges in modern cities and campuses. The present work highlights a cooperative decision making framework that integrates Dual Rough Sets (RS), Real Interval Order Relations and Neutrosophic Sets (NS) within a Multi-Criteria Decision-Making (MCDM) approach. Shannon Entropy serves to determine objective weights and multiple similarity measures such as Jaccard Similarity, Hamming Distance and Cosine Similarity improve robustness in evaluation. The three NS’s are Single-Valued (SVNS), Interval-Valued (IVNS) and Pythagorean (PNS), all of which are systematically applied and compared. The framework is validated by real-time data on sustainability criteria (for example, population, modes of transport, trip length and vehicle density) from twelve metropolitan Indian cities. Delhi is consistently recognized as the most sustainable city, followed by Bangalore and Ahmedabad, while the worst-performing cities were Bhopal and Indore. The stability of rankings across different neutrosophic environments is confirmed through sensitivity analysis of the metropolis. The framework represents a consistent and flexible decision-making tool for sustainable transportation planning in the face of uncertainty, considering the combination of cutting-edge similarity measures, composite entropy-based weighting and neutrosophic reasoning, it provides decision-making support for transparency and adaptive decision-making processes at both campus and urban levels.