An integrated recycling facility selection using neutrosophic TOPSIS for sustainable biomedical waste management.

The rapid increase in biomedical waste (BMW) generation driven by population growth and expanding healthcare services, especially in developing countries, has revealed significant gaps in sustainable waste management, particularly in the underutilization of recyclable components. Improper handling of recyclable waste leads to increased costs and resource depletion. Most hospitals and medical institutions rely on disposal-based strategies, overlooking the potential for recycling to reduce environmental impact and operational expenses. This study advocates recycling to improve profits and reduce environmental harm by proposing a hybrid decision-support framework that uses neutrosophic fuzzy TOPSIS (NFTOPSIS) to choose the best location for a facility that includes both a warehouse and a recycling unit, along with a multi-objective solid transportation problem (MOSTP) model to make recycling logistics more cost-effective and time-efficient. The single-valued hexagonal neutrosophic numbers are used to represent the uncertain real-world parameters. The neutrosophic compromise programming technique is implemented in the IBM CPLEX optimization studio to determine the trade-off solution between cost and time. A real-world case study in Vellore, Tamil Nadu, demonstrates the model's effectiveness. Results show significant reductions in recycling time and cost under two scenarios, with and without penalty constraints, highlighting that regulatory compliance significantly reduces unnecessary expenses. Sensitivity analysis confirms the model's robustness to parameter variations. The proposed framework offers a novel, uncertainty-resilient solution for sustainable and regulation-compliant BMW recycling operations while promoting the circular economy in healthcare.