Designing reverse logistics network for healthcare waste management considering epidemic disruptions under uncertainty.

Population growth and recent disruptions caused by COVID-19 and many other man-made or natural disasters all around the world have considerably increased the demand for medical services, which has led to a rise in medical waste generation. The improper management of these wastes can result in a serious threat to living organisms and the environment. Designing a reverse logistics network using mathematical programming tools is an efficient and effective way to manage healthcare waste. In this regard, this paper formulates a bi-objective mixed-integer linear programming model for designing a reverse logistics network to manage healthcare waste under uncertainty and epidemic disruptions. The concept of epidemic disruptions is employed to determine the amount of waste generated in network facilities; and a Monte Carlo-based simulation approach is used for this end. The proposed model minimizes total costs and population risk, simultaneously. A fuzzy goal programming method is developed to deal with the uncertainty of the model. A simulation algorithm is developed using probabilistic distribution functions for generating data with different sizes; and then used for the evaluation of the proposed model. Finally, the efficiency of the proposed model and solution approach is confirmed using the sensitivity analysis process on the objective functions' coefficients.

Sustainable circular supplier selection: A novel hybrid approach.

Circular supplier selection is the process of selecting suppliers in a closed-loop supply chain. Sustainable circular supplier selection addresses the social and environmental concerns in circular supplier selection problems. In this paper, for the first time, we combine the fuzzy best-worst method and the interval VIKOR technique to evaluate and prioritize sustainable suppliers in circular supply chains. The evaluation criteria are classified into three categories of economic, social, and circular factors extracted based on the domain expert's opinions. The fuzzy best-worst method is used to weigh the criteria, and the interval VIKOR technique is applied to evaluate the suppliers in the presence of uncertainty. This study contributes to the sustainable development goals (SDG's) of providing Decent Work and Economic Growth (SDG 8) and Responsible Consumption and Production (SDG 12). The proposed method is then used to evaluate six suppliers in the wire-and-cable industry in Iran. The results obtained from the implementation of the proposed approach and its sensitivity analysis indicate the applicability and efficiency of the proposed approach.