Abstract

Supply chain design is a crucial strategic solution that significantly impacts competitiveness, economic development capabilities, and overall economic growth. Ineffective supply chain design can lead to instability within the supply chain. The design of a reverse logistics network (RLN) is both strategic and highly challenging. As environmental sustainability becomes increasingly important, there is a growing emphasis on Closed-Loop Supply Chains (CLSC), which aim to recover value from end-of-life (EOL) products while promoting both economic and environmental sustainability. However, creating an effective CLSC involves significant challenges due to uncertainties such as demand fluctuations, return rates, and return quality. Furthermore, despite extensive research on CLSC models, critical gaps persist, especially regarding the integration of uncertainty management, the optimization of multi-objective trade-offs, and the incorporation of real-time decision-making in CLSC operations. This study conducts a systematic review of 42 published papers from 2013 to 2023, examining key aspects of CLSC models, including complexity, model type, data characteristics, time dynamics, optimization methods, and solution approaches. The findings reveal that existing studies predominantly focus on deterministic models, with limited emphasis on stochastic approaches, machine learning integration, and dynamic adaptation to changing market conditions..

Keywords: Closed loop supply chain,end of life,  return rates, return quality