This study develops a deterministic multi-period mixed-integer programming model for the strategic design and operational planning of multi-echelon Closed-Loop Supply Chain (CLSC) networks. The formulation integrates forward and reverse logistics flows within a unified optimization framework, encompassing manufacturing facilities, potential distribution centers, customer demand zones, prospective collection centers, and designated disposal facilities. The model captures critical network design decisions, including capacity-level selection for potential facilities, production and remanufacturing quantities, inter-echelon shipment volumes, inventory dynamics, and end-of-life product disposition, while enforcing constraints on capacities, flow conservation, and recovery/scrap ratios. The objective function minimizes the aggregate cost of production, transportation, processing, remanufacturing, disposal, and facility establishment. A synthetic dataset is employed to illustrate the framework, and the results demonstrate that the proposed model yields efficient network configurations and balanced flow allocations. Overall, the formulation offers a rigorous and adaptable foundation for cost-effective closed-loop supply chain design.

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