A framework of LR fuzzy AHP and fuzzy WASPAS for health care waste recycling technology

Abstract

Migration from a linear to a circular economy (CE) has become inevitable to reduce waste by making reusable products and materials. The present health care waste (HCW) management development has also been reformed due to this change. Since there is a strong connection between HCW management and CE, in this study, the HCW recycling technology selection problem has been addressed, modeled, and solved using the MCDM technique for the first time. In this paper, we present a new group decision-making process (GDMP) by combining the analytical hierarchy process (AHP) and weighted aggregated sum product assessment (WASPAS) under a fuzzy environment. LR fuzzy numbers (LRFNs) are employed to convey and model the linguistic judgments made by decision-makers (DMs). Novel LR fuzzy geometric mean, defuzzification method for the LRFNs, and LR fuzzy consistency checking method have been introduced here. The proposed technique is then applied to select optimal HCW recycling technology by considering nine selection criteria and four recycling alternatives based on the expert’s judgment. The proposed approach elicits an effective way of reusing the disposable HCW in conjunction with CE with the help of GDMP. To confirm the reasonableness, practicality, and applicability of the proposed methodology, an illustrative case study on several district hospitals in Tripura, India, has been performed. The validity, consistency, and robustness of the proposed approach have been checked through comparative and sensitivity analyses. The computational complexity of the proposed method has also been investigated and compared with some existing techniques. The research findings show that the proposed model has identified Red2Green as the best HCW recycling technology in the socio-economic perspective of Tripura, India.