A BIPOLAR NEUTROSOPHIC OPTIMIZATION MODEL FOR A MEDICAL WASTE SUPPLY CHAIN NETWORK DESIGN

Abstract

With scientific advancements, healthcare institutions and the services they provide are growing rapidly, which ultimately leads to greater production of medical waste. The potential problems and risks of medical waste have become more prominent as it causes inevitable harm to human health, the environment, and socio-economic sustainability. Proper management of medical waste requires sound planning at each phase of collection, transfer, sorting, storage, processing, and disposal. Any mismanagement in this process could lead to contamination and injury. Medical waste management system requires decision-making on locating facilities and managing inventory and transportation. Traditional waste disposal methods have exhibited inefficiencies, contributing to increased operational costs, escalated risk factors, and heightened environmental degradation. Addressing these multifaceted challenges demands a paradigm shift in waste management practices. In recently published research optimization of medical waste supply chain is an uncommon area of focus. As well as sustainability and environmental impacts are rarely taken into consideration. In the realm of efficient healthcare waste management, the optimization of the medical waste supply chain is crucial that integrates environmental, social, and economic aspects. In this research a Mixed Integer Linear Programming (MILP) model is developed to design a Medical Waste Supply Chain Network (MWSCN). A multi-objective model is designed where the first objective function aims to minimize transportation cost, storage and sortation cost, fixed cost, and processing cost. The second objective function aims to maximize the Risk Priority Number (RPN). The third objective function aims to minimize CO2 emissions resulting from medical waste transportation and processing. A Bipolar Neutrosophic Optimization Model (BNOM) approach is utilized to address these multi-objective challenges in this domain. Leveraging the unique properties of Bipolar Neutrosophic Modeling, the proposed BNOM aims to accommodate uncertainties and vagueness intrinsic to medical waste management. By integrating this multi objective model, the study endeavors to offer an innovative and comprehensive solution that optimizes the medical waste supply chain network design. A real-world case study of a medical waste supply chain network was undertaken to demonstrate the potential of the suggested model, which includes 10 hospitals, 1 central transfer station, 3 incineration facilities, 2 recycling facilities, and 2 landfill sites in Lahore, Pakistan. The model was implemented by the MATLAB software package and solved by the BNO method. Finally, sensitivity analysis was conducted to analyze the impact of changes in fuel price, segregation ratio, and distance on the optimal medical waste supply chain network and the results are discussed.