In this study, a multi-period Mixed Integer Linear Programming is developed to optimize a closed-loop supply chain in the plastic box manufacturing industry. The supply chain includes multiple product types, a production center, several Distribution centers (DCs), and Original Equipment Manufacturers (OEMs) as the final consumers. The distribution centers handle the management of new products, returned products in good condition, and products requiring refurbishment. The model assumes predetermined locations for production and distribution centers and focuses on optimizing resource allocation and material flow over several consecutive time periods. The primary objective is to minimize the total costs related to production, refurbishment, inventory holding, transportation, raw material procurement, and electricity consumption. The model incorporates periodic constraints on electricity quotas and stepwise discounts on raw material purchases. Additionally, penalty costs associated with product shortages and environmental costs arising from production and refurbishment processes are considered. The results demonstrate that the proposed multi-period approach effectively ensures optimal resource allocation in each period and significantly reduces the total costs of the closed-loop supply chain. Specifically, when a similar model is implemented without accounting for the return of healthy and refurbished products, costs increase substantially. Moreover, the model facilitates improved product lifecycle management and reduces environmental impacts through effective management of the returned product flows.

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