Abstract: In view of the rapid development of China’s new retail model and fuzzy uncertainty of consumers’ demand and return for fresh products, considering the decision of the minimum total logistics cost, the best facility location and the optimal vehicle route, a fuzzy programming model of closed-loop logistics network is established for fresh products under new retail model. In order to solve this model, the quantities of consumers’ demand and return are regarded as triangular fuzzy parameters and the fuzzy constraints are transformed into crisp equivalent by applying the fuzzy chance constrained programming. Through the case of the fresh e-commerce of Shanghai, the feasibility and effectiveness of the proposed model are verified by adopting the sensitivity analysis of the confidence level and the calculation of genetic algorithm and particle swarm optimization algorithm, which provides a reference for relevant decision makers.

Key words: new retail, fresh products, closed-loop logistics network, fuzzy chance constrained programming, genetic algorithm, particle swarm optimization algorithm

摘要： 针对我国新零售模式的快速发展，消费者对生鲜产品需求与退货的模糊不确定性问题，考虑最低物流总成本、最佳设施选址以及最优配送车辆运输路径的决策，构建了新零售下生鲜产品闭环物流网络模糊规划模型。为求解该模型，将需求量与退货量看成三角模糊参数，利用模糊机会约束方法将模糊约束转化为等价的清晰条件。以上海市某生鲜电商企业为实例，通过置信水平的敏感性分析以及遗传算法与粒子群算法的双求解，验证了模型的有效性与可行性，进而为相关决策者提供了借鉴。

关键词: 新零售, 生鲜, 闭环物流网络, 模糊机会约束规划, 遗传算法, 粒子群算法