Abstract: In view of the current research on vehicle routing of cold chain logistics, the impact of traffic congestion on operation cost is not fully considered. This paper integrates the road congestion factors into the mathematical models of green vehicle routing for cold chain logistics. Balancing the economic costs and environmental costs, comprehensive consideration in a time-varying network should be taken into account of vehicle management costs, cost of energy consumption during transportation, cargo damage costs, refrigeration costs, and penalty costs for customer demand time windows. And at the same time, introducing carbon emission costs during transportation and refrigeration, and the overall arrangement of vehicle routes can reduce overall operating costs for logistics companies, resulting in greener environmental protection. On this basis, an improved ant colony algorithm is designed to solve the problem according to the characteristics of the model, and to simulate the models and algorithm with examples. Verification of the model and method can effectively avoid the congestion in rush hour, lower delivery cost, promote energy saving and emission reduction, and provide effective advice for the cold chain logistic companies in route-distribution decision.

Key words: cold chain distribution, traffic congestion, green vehicle routing problem, path?dividing, carbon footprint, improved ant colony algorithm

摘要： 针对目前研究冷链物流车辆路径问题多未考虑交通拥堵对运营成本的影响，将道路拥堵因素融入到冷链物流绿色车辆路径（Green Vehicle Routing Problem）优化数学模型中。兼顾经济成本和环境成本，在时变网络下综合考虑冷链物流中车辆管理成本、运输能耗成本、货损成本、制冷成本以及客户需求时间窗的惩罚成本，同时引入运输和制冷过程中产生的碳排放成本，统筹安排车辆路径，使得物流企业整体运营成本最低，更绿色环保。在此基础上根据模型特点设计改进蚁群算法进行求解，用实例对模型和算法进行仿真，验证该模型和方法可以有效地规避拥堵时段，降低配送成本，促进物流企业的节能减排，可以为物流企业冷链配送路径决策提供良好的参考依据。

关键词: 冷链物流配送, 交通拥堵, 绿色车辆路径, 分段规划, 碳排放, 改进蚁群算法