Modeling circular supply chains as an approach for waste management: A systematic review and a conceptual framework

Abstract

All world countries are suffering from repercussions of the global climate change problems and there is an urgent need to mitigate their negative impacts. Improper waste management methods contribute directly to climate change where common waste treatment methods are basically relying on incineration or landfilling. Nowadays, incorporating the circular economy perspective into the business model demonstrates the ability of creating value from wastes and reducing the residuals by adopting the circular supply chains management (CSCM) as a promising alternative to linear supply chains. Studying and analyzing the performance of CSCM through different modeling techniques are crucial stage for supporting decision making process where implementation of CSCM requires deep knowledge about challenges, important factors, and optimal values of critical decision variables. In response, this research presents a review about the proposed models that dealt with CSCM in each modelling field to give insights into models’ objectives and performances and outline the research gaps and future research directions for researchers. Furthermore, this study proposes a conceptual framework of reinforcement learning model which acts as an adaptive model for studying the dynamicity, complexity, and uncertainty in CSCM with respect to lot sizing problem that faces supply chains. This paper recommends further studies in the following areas which are important but received little or no attention: studying the dynamicity and stochastic nature of CSCM environment, conducting a forecasting analysis on important parameters of CSCM, designing a sustainable CSCM network, validating models of CSCM on real case studies.