Evaluating Public Bus Shelter Service Quality by Using Complex Neutrosophic Einstein Prioritized Operators

Abstract

A robust decision-making strategy is essential for efficiently collecting and evaluating complex data, yet in real-world urban settings, ambiguity often prevails. To address these challenges, this paper introduces a multi-criteria group decision-making (MCGDM) algorithm specifically designed for the complex single-valued neutrosophic (CSVN) environment. The CSVN framework offers greater consistency and reliability than intuitionistic fuzzy sets (IFS) by handling a triplet of truthiness, indeterminacy, and falsity, which better captures indeterminate and inconsistent human judgments. Recognizing the critical role of aggregation operators in synthesizing diverse criteria into a single evaluative value, we develop novel Einstein Prioritized Aggregation Operators (EPAO) for CSVN elements. Specifically, the complex single-valued neutrosophic Einstein prioritized weighted averaging (CSVNEPWA) and weighted geometric (CSVNEPWG) operators are presented, and their distinctive properties are examined. Leveraging these operators, a comprehensive MCGDM algorithm is constructed to navigate uncertain decision environments. As a real-world illustration, the model is applied to evaluate the quality of the public Metrobus system's shelter services in Istanbul, Turkey. Five distinct shelter alternatives are assessed against five strategic criteria: weather protection, seating comfort, cleanliness and maintenance, information systems, and safety and lighting by a panel of urban mobility experts. The results confirm the model’s capacity to prioritize infrastructure investments under deep ambiguity, offering a transparent, adaptive tool for transit authorities to enhance passenger experience.