中断风险下易腐品多目标闭环供应链网络模型

在当今全球化和高度不确定的商业环境中，供应链网络容易遭遇设施中断、路径中断等多重中断风险。同时考虑到易腐品需求波动大、易损耗、退货率高、处理不当会污染环境等问题，以最小经济成本、最小环境影响、最大社会效益为目标，提出缓解中断风险的策略并构建了不确定条件下易腐品多目标闭环供应链网络模型。为了减少不确定参数的影响，实现最优设施选址与最佳配送路径的决策安排，将易腐品需求量和退货量设定为三角模糊值，采用模糊机会约束方法解决模型中的不确定约束问题。以上海市某易腐品企业为例，通过遗传算法和粒子群算法对模型进行求解。结果表明，采用缓解中断风险的策略可以显著改善供应链网络在中断情况下的表现，且相对于单目标优化，多目标优化整体表现更优。

Multi-objective closed-loop supply chain network model for perishable products under disruption risk

Considering today''s globalized and highly uncertain business environment, the supply chain network is prone to the risk of disruption. At the same time, in view of the issues, such as demand fluctuation, high return rate and environmental pollution caused by improper treatment, the strategies to mitigate the interruption risk were proposed and a multi-objective closed-loop supply chain network model of perishable products under uncertain conditions concerning minimum economic cost, the minimum environmental impact and the maximum social benefit was constracted. In order to reduce the influence of uncertain parameters and realize the decision-making arrangement of the optimal facility location and the optimal distribution path, the demand and return quantity of perishable products were set as triangular fuzzy values, and the fuzzy constraints in the model were equivalently transformed into clear correspondences by using fuzzy chance constraint method. Taking a perishable product enterprise in Shanghai as an example, genetic algorithm (GA) and particle swarm optimization (PSO) algorithm were used to solve the model. The calculating results show that the performance of supply chain network can be significantly improved by using the strategy of mitigating disruption risk, and the overall performance of multi-objective optimization of closed-loop supply chain network is better than that of single objective optimization.