实物互联网环境下考虑供应中断的易腐品低碳生产-路径协同优化研究

Co-optimization of Low-carbon Production and Routing for Perishable Goods Considering Supply Disruptions in the Physical Internet

针对易腐品供应网络易受意外中断影响而造成设施能力和运输距离不确定性问题,探讨了具有全球开放和共享特征的实物互联网(physical internet,PI)环境下易腐品低碳生产-路径协同优化策略。PI作为一种相互连接、共享和适应性强的创新物流系统,在增强易腐品供应网络弹性和减少碳足迹方面具有巨大潜力。基于易腐品的特殊性和PI的特征,构建基于情景的两阶段随机规划模型。为了求解模型,设计集成情景生成与缩减和改进Benders分解的混合求解方法。最后,以辽宁供销安邦海得食品供应网络为背景进行算例分析,验证了模型的可行性和算法的有效性。敏感性分析结果表明,PI在减少碳足迹和增强供应链弹性方面具有显著优势。此外,本文还对碳排放交易机制、设施能力损失、运输距离增加以及产品生命周期的影响进行全面分析。本研究丰富了易腐品供应网络中低碳生产与路径协同优化的理论基础,也为物流企业应对不确定性和追求碳中和目标提供重要的理论指导。

To address the problem of uncertainty in facility capacity and transportation distances due to unexpected disruptions in supply networks of perishable goods,this study explores the co-optimization of low-carbon production and routing for perishables in the context of the globally open and shared physical internet(PI)environment.As an innovative logistics system characterized by connections,sharing,and adaptability,PI has great potential to enhance the resilience of perishables supply networks and reduce carbon footprints.A scenario-based two-stage stochastic programming model is developed based on the unique characteristics of perishables and the features of PI.To solve the model,a hybrid solution method integrating scenario generation and reduction with improved Benders decomposition is designed.Finally,a case study is carried out in the context of Liaoning Supply and Marketing Anbang Haider Food Supply Network to verify the feasibility of the model and the effectiveness of the algorithm.Sensitivity analysis results show that PI has significant advantages in reducing carbon footprints and enhancing supply chain resilience.Additionally,this study comprehensively analyzes the impacts of carbon emission trading mechanisms,facility capacity loss,increased transportation distances,and product lifecycle effects.This study not only enriches the theoretical foundation of low-carbon production and routing co-optimization in perishables supply networks but also provides important theoretical guidance for logistics companies in coping with uncertainty and pursuing carbon neutrality goals.