<![CDATA[This study reviews and compares two logistics models tailored to perishable goods, focusing on the spatial and temporal dimensions of supply chain optimization. The first model proposes a population-density-based location planning framework that applies network centrality measures to determine optimal order fulfillment center locations. The second model introduces a two-warehouse inventory policy designed to handle disruption scenarios, such as lockdowns, by balancing demand variation and spoilage rates. Both models were evaluated for their methodological approaches, performance under disruption, and adaptability. The integrated review underscores the necessity of combining spatial efficiency with dynamic stock resilience to improve supply chain effectiveness for perishable goods. Findings suggest that hybrid models leveraging both geographic and temporal decision layers can significantly strengthen logistics adaptability.]]>
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