Journal
WASTE MANAGEMENT
Volume 113, Issue -, Pages 197-209Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.wasman.2020.05.052
Keywords
Reverse Supply Chain; Medical Waste; Multi-objective; Fuzzy goal programming; Robust possibilistic programming
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Medical waste generation is rapidly rising, which may cause a serious risk for both humans and environment if it is not properly managed. Designing an efficient and reliable medical waste reverse supply chain (MWRSC) is extremely beneficial to society. Most studies on this issue have only considered the generated waste and have not reported the uncertainty in the amount of medical waste generation and other MWRSC parameters. Sustainability criteria and environmental issues in choosing treatment technology are rarely considered as well. In this research, a linear programming model under uncertainty is developed to design an MWRSC. The proposed model is multi-item and multi-period with three objective functions. The first objective function minimizes total costs, the second objective function is relevant to the best treatment technology selection and the third objective function minimizes the total medical waste stored. A robust possibilistic programming approach is utilized to handle imprecise parameters in the model and a fuzzy goal programming method is employed to build up a multi-objective model. A real case study is conducted to illustrate the potential of the proposed model which involves different attributes and problems, such as the location and capacity of facilities, and the type of treatment technology. Furthermore, the transferring amount of medical waste among different nodes is calculated. (C) 2020 Elsevier Ltd. All rights reserved.
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