An optimisation tool for strategic planning of multiple downgraded market levels in circular supply chain management

Recent legislation promotes the adoption of Circular Economy principles in supply chain design, to encourage reuse, remanufacture, and recycle end-of-life products. An efficient circular supply chain design can improve resource efficiency, extend product lifecycles, and reduce waste, providing competitive advantages while contributing to sustainability goals. This study develops a bi-objective mixed-integer linear programming model to optimise strategic decisions in circular supply chain design, including activation of downgraded market levels, facility locations, and product flows. The model also accounts for the impact of cannibalisation between new and recovered product demand. The improved version of the augmented epsilon-constraint method (AUGMECON2) is applied to solve the model. Numerical experiments and sensitivity analyses validate the performance of the model and provide managerial insights to practitioners. The results demonstrate the potential of the model to support strategic decision-making and enhance circular supply chain effectiveness.