A hybrid multi-criteria decision-making and fuzzy stochastic chance-constrained optimization approach for determining the location of healthcare waste (HCW) disposal facilities

Abstract

Effective management of healthcare waste (HCW) disposal is an ongoing challenge for healthcare providers and urban municipalities, particularly in densely populated areas. This study presents a novel framework for selecting optimal HCW disposal sites by integrating a fuzzy multi-criteria decision-making method with a fuzzy stochastic chance-constrained optimization approach. The framework provides a robust, data-driven methodology for determining the best disposal sites by balancing multiple criteria under uncertainty. To ensure a comprehensive and reliable selection process, 36 criteria were identified through a rigorous literature review and expert consultations. These criteria were then grouped into five primary categories: environmental, social, economic, technical, and geological. A case study was conducted in Chicago—a densely populated area with complex healthcare demands and varied environmental and logistical considerations - to demonstrate the applicability of this framework in an urban setting.Our results show that the proposed method outperforms traditional fuzzy AHP models in both robustness and simplicity, providing a more adaptable and efficient solution for HCW disposal site selection. This research contributes a practical and scalable tool for urban municipalities and healthcare institutions, supporting informed decision-making to improve public health and environmental outcomes.