Sener, Nazmi2026-01-242026-01-242024978-3-031-70017-0978-3-031-70018-72367-33702367-3389https://doi.org/10.1007/978-3-031-70018-7_71https://hdl.handle.net/20.500.12868/5490International Conference on Intelligent and Fuzzy Systems (INFUS) -- JUL 16-18, 2024 -- Istanbul Tech Univ, Canakkale, TURKEYThe Spherical Fuzzy Green Hub Covering Flow Problem (SFGHCFP) represents a novel multi-layered analytical approach designed to optimize the sustainability and efficiency of hub-based distribution networks. This paper introduces an innovative framework that integrates the principles of spherical fuzzy logic with green logistics, addressing the complexities of strategic decision-making in dynamic and uncertain environments. The methodology encapsulates a series of advanced spherical fuzzy aggregation operators that support multi-period decision-making (MPDM) in supply chain management. By incorporating environmental considerations into the hub location-routing problem, the SFGHCFP seeks to minimize the carbon footprint and ecological impact of logistical operations, while ensuring cost-effectiveness and adherence to service level agreements. The study proposes a unique hybrid model that evaluates potential hub sites and routes, accounting for varying degrees of membership, hesitation, and truth valuation inherent to fuzzy set theory. Furthermore, the spherical fuzzy parameters are calibrated to assess and prioritize green criteria, facilitating the development of a sustainable hub network design. The effectiveness of the proposed SFGHCFP model is demonstrated through a series of computational experiments that simulate real-world scenarios of goods distribution. The results reveal significant enhancements in both ecological sustainability and operational efficiency, showcasing the potential of the spherical fuzzy-based approach in rendering the logistics of city supply chains more environmentally conscious without forfeiting service quality. The practical implications of this research extend to industries seeking green optimization of their logistics networks, proving that environmentally responsible practices can be integrated effectively in complex multi-period logistical planning.eninfo:eu-repo/semantics/closedAccessHub CoveringSpherical FuzzyMathematical ModelingConference Object10.1007/978-3-031-70018-7_7110886416482-s2.0-85203581257Q4WOS:001331332200070N/A