<p>The effective management of humanitarian supply chains constitutes a fundamental challenge in disaster response operations. This paper puts forward a comprehensive optimization framework to guide logistical decisions within a multi-echelon, multi-product relief network. In this work a multi-period, mixed-integer linear program designed to identify an optimal, least-cost operational plan by navigating the challenging compromises required in disaster relief scenarios. The key contributions of the model lie in its integration of realistic operational features, including a novel risk-adjusted transportation cost based on infrastructure damage, echelon-specific inventory holding logic, and a practical dual-shortage mechanism that allows for both tactical local purchasing and strategic distant supplier purchase of unmet demand. Applying our model to a large-scale scenario reveals a critical insight: physical throughput capacities, rather than budget or storage space, are the dominant system bottlenecks. These constraints force a reliance on local procurement and expensive procurement from a distant supplier to avoid shortages, quantifying the difficult balance between cost and service level. The research offers a robust decision-support tool and provides clear managerial insights, arguing that preparedness efforts should prioritize enhancing logistical throughput over static storage capacity and formalizing local supplier agreements.</p>