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Urban transportation systems, characterized by inherent uncertainty and ambiguity, present a formidable challenge in decision-making due to their complex interplay of factors. This complexity arises from dynamically shifting commuter behaviors, a diverse array of transit options, and variable traffic patterns. Such unpredictability hinders the formulation and implementation of effective strategies. Addressing this challenge necessitates innovative problem-solving methodologies capable of handling the nuanced uncertainties present in these systems. This study introduces the multidimensional neutrosophic fuzzy hypersoft set (MDNFHS) as a groundbreaking method for managing ambiguity in urban transportation planning. MDNFHS, emerging from the integration of neutrosophic fuzzy sets (NFSs) and hypersoft sets (HSs), uniquely encapsulates both the degrees of membership and non-membership. It is demonstrated that the tailored set-theoretic operations and distance measurements specific to MDNFHS enable enhanced manipulation and analysis, making it a potent tool in complex decision-making scenarios. The efficacy of MDNFHS in decision-making is exemplified through a compelling case study, showcasing its ability to offer clarity in situations marred by ambiguity. This novel approach is posited to revolutionize decision-making processes, offering a new level of certainty in environments traditionally dominated by uncertain elements.
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Saeed et al. (2023) studied this question.
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