Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy

Abstract

Against global industrial upgrading and China’s “dual-carbon” policy, the cold chain for fresh products faces numerous challenges such as supply disruptions, demand fluctuations, and low-carbon transformation. This study focuses on introducing the key optimization goals of the cold chain network for fresh products: maximizing the service level while minimizing operating costs and carbon emissions. To this end, this study proposes a high-dimensional multi-objective optimization model for the cold chain network of fresh products and designs four resilience strategies to address supply disruption and demand fluctuation scenarios. To solve this model, this study innovatively designs a hybrid algorithm combining neighborhood search and swarm intelligence, integrating the advantages of local exploration and global optimization to balance the relationships among multiple objectives efficiently. In addition, this study conducts a real-world case analysis to verify the effectiveness of the proposed model and the algorithm. Furthermore, by deeply exploring the comprehensive impacts of supply disruptions and demand fluctuations on the cold chain network for fresh products, the mechanism of action of resilience strategies in dealing with supply chain risks is highlighted. The research results provide valuable decision-making support for fresh cold chain enterprises to develop resilient and low-carbon network optimization strategies for cost reduction, efficiency improvement, and sustainable development.