Abstract: In order to improve the transportation efficiency of cold chain logistics and achieve the low-carbon goal of energy saving and emission reduction, this paper discusses the multi-objective low-carbon cold chain vehicle routing problem in cold-chain logistics distribution (MOLCVRPCLD). Compared with the existing literature, this paper considers a more low-carbon mixed fleet of electric vehicles and fuel vehicles, and establishes an optimization model with the goal of optimal comprehensive cost and minimum carbon emissions. Comprehensive cost includes fixed cost of vehicles, time window cost, cargo damage cost, fuel consumption cost and power consumption cost. Carbon emissions includes fuel emissions and refrigeration emissions. According to the characteristics of the model, a non-dominated sorting genetic algorithm II (NSGA-II) is designed to solve the model. And genetic algorithm (GA) is used to optimize the two targets respectively to verify the effectiveness of the model and algorithm.

Key words: low-carbon cold chain, mixed fleet, electric vehicles, non-dominated sorting genetic algorithm II (NSGA-II)

摘要： 为提高冷链物流运输效率，实现节能减排的低碳目标，探讨了多目标低碳冷链车辆路径问题（multi-objective low carbon vehicle routing problem in cold-chain logistics distribution，MOLCVRPCLD）。与现有文献相比，考虑了更为低碳的电动车与燃油车混合车队，建立了以综合成本最优、碳排放最小为目标的优化模型。其中，综合成本包括车辆的固定成本、时间窗成本、货损成本、油耗成本、耗电成本，碳排放包括燃油碳排放和制冷碳排放。根据模型特点，设计了贴合模型的非支配排序遗传算法（non-dominated sorting genetic algorithm II，NSGA-II）对该模型进行求解，并利用遗传算法（genetic algorithm，GA）分别对两个目标进行优化以验证模型和算法的有效性。

关键词: 低碳冷链, 混合车队, 电动车, 非支配排序遗传算法（NSGA-II）