A novel near-to-expiry waste reduction model with smoothing ordering policy and retail discounting for food supply chains
提出一个优化临期食品供应链成本的模型，通过平滑订购策略和零售折扣减少浪费，并开发了智能变邻域搜索算法来求解问题。
This study presents a novel model for optimizing costs and reducing food waste in near-to-expiry (NTE) food supply chain (FSC) networks. The proposed approach involves direct product dispatch from manufacturers to distribution centers (DCs) and retailers through vehicle routing. The model incorporates a smoothing ordering policy and retail discounting to minimize waste by aligning purchasing decisions with real-time customer demand. A new metaheuristic, smart variable neighborhood search (SVNS) algorithm, is developed to address this problem. The SVNS algorithm dynamically selects neighborhood structures (NSs) to improve computational efficiency and solution quality. The performance of SVNS is evaluated against traditional benchmark methods through various experimental scenarios. The results show that the SVNS algorithm outperforms conventional benchmarks for managing near-expiration products.