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Coronavirus disease 2019 (COVID-19) brings about severe disruptions for human living, economics, and environmental balance. This pandemic has boosted the demand for personal protective equipment (PPE) and thus, medical wastes. Thus, a research hypothesis is stated whether it would be possible to provide more efficient distribution and inventory planning to optimize the PPE availability in a fuzzy environment. To confirm the hypothesis, in addition to addressing a scientific novelty considering integration of linear programming with fuzzy parameters, named as the Jimenez’s method and clustering heuristic methods, the practicality of these approaches is provided on a real case study and generated instances from Turkey. The computational results reveal that clustering the 32% of the hospitals ensures optimum total cost and solution time while feasibility degree changes between 0, 4, and 1 values of the Jimenez are not more effective on the results. Improved cost results reveal the economic importance of the healthcare supply chain management and optimal PPE distribution and inventory planning can break down the disease propagation and reduce the detrimental impacts on human life. The proposed approach, for the first time, ensures practical and theoretical insights of distribution and storage decisions across disciplines, namely, engineering and health-care organization authorities.

energy sources, part a: recovery, utilization, and environmental effects

Linear programming with fuzzy parameters for inventory routing problem in effective management of personal protective equipment: a case study of corona virus disease 2019