A fuzzy sustainable model for drug supply chain networks during a pandemic

Abstract

This research focuses on developing a fuzzy sustainable model for drug supply chain networks during a pandemic. The outbreak of a pandemic introduces unprecedented uncertainties and complexities to the drug supply chain, necessitating the integration of sustainability considerations and fuzzy logic techniques into decision-making processes. The proposed model aims to optimize decision variables, such as inventory levels, production capacities, transportation routes, and allocation strategies, while balancing conflicting objectives and addressing sustainability criteria. The model incorporates fuzzy logic to handle imprecise and uncertain inputs, allowing decision-makers to capture qualitative information and expert knowledge. The research emphasizes the importance of sustainability in drug supply chains, encompassing environmental impact, social welfare, and economic viability. Through the use of an optimization framework and a decision support system, stakeholders can make informed decisions considering sustainability criteria and dynamic pandemic conditions. The research contributes to enhancing the resilience, efficiency, and sustainability of drug supply chains during pandemics, facilitating better patient care and community well-being.