Rolling Horizon Optimization of Allocation-Location in Agricultural Emergency Supply Chains

Ensuring the smooth production and distribution of agricultural products is a crucial pathway to achieving a balance between supply and demand. However, the information within the agricultural product supply chain is characterized by its dynamic and asymmetric nature, compounded by frequent outbreaks of infectious diseases that lead to supply interruptions and allocation difficulties. These factors collectively undermine the operational efficiency and resilience of the agricultural product supply chain. This study develops an integrated allocation-location optimization model for emergency agricultural product supply chains based on a rolling horizon approach. The model accounts for both supply shortage and sufficient scenarios, with objectives to maximize the comprehensive material satisfaction rate, minimize the activation cost of distribution centers, and minimize allocation time. The proposed model is solved using the Benders decomposition algorithm. Finally, a case study based on the Shanghai pandemic outbreak is conducted for numerical simulation. The results demonstrate the effectiveness of the model: the comprehensive material satisfaction rate increases progressively over the rolling periods, rising from approximately 84% in period 1 to 100% by period 3. Furthermore, fairness analysis confirms that the model also effectively ensures equitable distribution of supplies.