Cost optimization in closed-loop supply chain network design: a multi-period MILP model incorporating discount incentives and environmental awareness

This study develops a multi-period Mixed Integer Linear Programming model for Closed-Loop Supply Chain (CLSC) network design in the electronics sector. The model explicitly integrates two dynamic drivers of consumer behavior—discounts and environmental awareness—into the return rate formulation. The model defines the flow of production, remanufacturing, shipping, returned product quantity, waste volume, and consumer return rate across multiple planning periods, with the goal of minimizing total costs. The numerical case study is based on synthetic data constructed based on parameter ranges in previous CLSC studies to reflect realistic operational conditions. The numerical results show manufacturing costs as the largest component (68.36%), followed by transportation (8.23%) and distribution handling (6.69%). Sensitivity analysis indicates (i) higher discounts and greater awareness significantly increase the return rate, increase remanufacturing volume, and reduce waste; and (ii) increasing Fd results in significant cost savings, with the highest outcome minimizing combined production and remanufacturing costs. These findings support a targeted strategy of discounts and environmental awareness, aligning remanufacturing capacity with returns, and achieving profitability. For policymakers, this model offers a decisionsupport tool to assess discounts and awareness programs, encouraging sustainable and profitable CLSC operations that align with circular economy principles.