MODELLING AND ANALYSIS OF A REVERSE LOGISTICS DECISION SUPPORT SYSTEM FOR BIOMEDICAL WASTE MANAGEMENT

Abstract

The growing waste in healthcare facilities has drawn attention from decision-makers around the world, as it has a substantial impact on both public health and the environment. The crucial factors driving the development of these wastes are an increasing population, rising healthcare facilities to serve patients, and uncontrolled infectious diseases. The type of healthcare establishments and level of treatment provided in medical facilities affect the quantity and quality of waste produced. These wastes are commonly disposed of in violation of the law in developing countries by mixing common waste with unsegregated Healthcare Waste (HCW), endangering the health and safety of the general public. The lack of knowledge about disposal methods and policies among the personnel and residents makes it difficult to handle waste effectively. Additionally, the hazardous emissions produced while treating these wastes damage the air, water, and land and thus lead to health issues. These factors have caused the World Health Organization (WHO) and researchers to focus on finding practical and successful approaches to manage these wastes. Despite the enormous efforts made by the regulatory organizations and waste handlers, the countries are having difficulty managing waste effectively and efficiently. Thus, it is necessary to address the issues brought on by handling these wastes and offer regulatory authorities’ suggestions for enhancing the current waste management system. Thus, the primary purpose of this study is to model and analyze the Healthcare Waste Management (HCWM) system so that decision-makers may use it to build and improve the existing system. It is necessary first to identify the key waste management strategies and challenges to accomplish this goal. A thorough literature review and field survey were carried out to do this. Our first objective is to develop a composite index for assessing the effectiveness of a waste management system. The designed conceptual framework, which acts as the building block for the index, interlinks the technical, managerial, and sustainability dimensions. The significant sub-indicators are analyzed for India’s northern and southern states. The developed index allows for comparing the management practices among the states and highlights the alarming situation. The robustness of the model is validated by performing sensitivity and cluster analysis for its intended use in decision-making. Our next objective of the research is to address the environmental burden of existing and proposed waste scenarios. The model is developed using Life Cycle Assessment (LCA) approach using SimaPro software. The CML-IA baseline impact assessment method is utilized to evaluate the environmental impacts. The reliability of the model is tested using sensitivity and uncertainty analysis. The analysis identifies the influential key processes, parameters, and impact categories. The model helps the decision-makers to make strategic decisions to reduce the environmental burden. The study's final objective is to model the waste collection system to optimize vehicle routes and save transportation costs. A hybrid metaheuristic algorithm is designed to solve the model. The devised technique combines genetic operators with ant colony foraging behavior to enhance computational efficiency. The effectiveness of the proposed algorithm is tested on 29 benchmark test instances and an actual case study for collecting biomedical waste in the northern part of India. The developed algorithm can assist waste collectors in offering vehicles the most efficient routes, thus reducing travel expenses. The study findings will provide crucial solutions that regulatory agencies can use to measure and enhance HCWM performance. To sum up, several recommendations that will aid governmental entities in successfully and efficiently managing waste have been addressed in the conclusion section.