Abstract: In view of the rapid development of China's carbon trading market,the increasing distribution demand of cross-regional e-commerce and the returned demand of fresh food caused by short shelf life and spoilage,a two-stage cross-regional closed-loop logistics network and the vehicle routing optimization model were proposed for fresh food e-commerce under the environment of carbon trading.Through the case of the fresh food e-commerce of Suzhou,the validity of the proposed model was verified by adopting Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm.Furthermore,a good reference could be provided for building the cross-regional forward and reverse logistics network for e-commerce as well as minimizing the operation costs of system under the carbon trading environment through this research.

Key words: carbon trading, fresh food e-commerce, cross-regional logistics network and route planning, closed-loop, genetic algorithms, particle swarm optimization

摘要： 针对我国目前碳交易市场的迅猛发展、跨区域电商配送需求的增加以及生鲜产品因保质期短、易损耗而产生的退货需求,构建了碳交易环境下两阶段生鲜电商企业跨区域闭环物流网络及配送车辆路径优化模型。以苏州市生鲜电商企业为实例,采用遗传算法和粒子群优化算法验证了该模型的有效性。该研究成果为碳交易环境下构建跨区域正逆向电商物流网络及降低系统运营成本提供了借鉴。

关键词: 碳交易, 生鲜电商, 跨区域物流网络及路径规划, 闭环, 遗传算法, 粒子群优化算法