Sustainable urban logistics optimization using an integrated q-rung orthopair fuzzy aczel–alsina heronian mean framework

Urban logistics systems refer to the effective planning and optimization of freight transportation in congested urban areas, balancing economic factors and environmental protection. Modern cities demand advanced, technology-based urban logistics systems and intelligent transportation systems to meet increasing customer demand and the rapid growth of urban populations in Dublin. Selection of an efficient urban logistics system remains challenging due to the complexity of urban environments and conflicting operational requirements. Therefore, an intelligent decision-making framework is required to integrate relationships among conflicting factors based on uncertain expert knowledge to support low-carbon logistics solutions and reliable transportation planning and management. This study proposes an advanced decision-making framework based on the weighted aggregated sum product assessment (WASPAS) method, an intelligent optimization approach that efficiently incorporates expert assessments and multiple conflicting factors related to logistics service providers. Several aggregation operators are formulated to explore relationships among conflicting criteria, including the q -rung orthopair fuzzy ( q -ROF) Aczel–Alsina Heronian mean, the weighted Heronian mean, the geometric Heronian mean, and the weighted geometric Heronian mean, all of which possess desirable mathematical properties. Moreover, intelligent integrated decision-making algorithms for multi-attribute decision-making (MADM) problems are established to handle uncertainty in complex real-world problems. To showcase the validation and compatibility of the proposed methodologies, an illustrative numerical case study focusing on urban logistics in Dublin is conducted to evaluate alternative solutions. A comparative analysis demonstrates the effectiveness, flexibility, and superiority of the proposed approach over existing methodologies for supporting sustainable and resilient urban logistics planning.