摘要
针对冷链物流高时效性、高成本的特点,运输和冷藏过程中的碳排放成本,以及违反时间窗的惩罚成本等因素,构建以配送总成本最小化为目标的冷链物流配送路径模型,并采用改进的自适应遗传算法进行求解。通过实证分析,对运输路径和运输车辆进行决策,并针对优化前后的结果进行分析,验证了模型和算法的有效性。结果表明:优化后的总配送成本相较于优化前减少了16.55%,碳排放成本相较于优化前减少了2.22%,优化后的遗传算法在降低配送成本和碳排放成本上具有显著效果,可以通过合理安排配送路径及运输车辆等手段来降低配送成本和碳排放成本。
Aiming at the characteristics of high timeliness and high cost of cold chain logistics,the cost of carbon emission in the process of transportation and cold storage,and the penalty cost of violating the time window,and other factors,the paper constructed a cold chain logistics distribution path model with the goal of minimizing the total cost of distribution,and used the improved adaptive genetic algorithm to solve the problem.Through the empirical analysis,the decision-making of the transportation path and transportation vehicles was carried out,and the results before and after the needle optimization were analyzed to verify the effectiveness of the model and algorithm.The results show that the total distribution cost after optimization is reduced by 16.55%compared with the pre-optimization,and the carbon emission cost is reduced by 2.22%compared with the pre-optimization,and the optimized genetic algorithm has a significant effect on reducing the distribution cost and carbon emission cost,which can be reduced by means of reasonable arrangement of distribution paths and transportation vehicles.
作者
万君
王雪
黄建成
WAN Jun;WANG Xue;HUANG Jiancheng(Liaoning Technical University,Huludao 125000,China)
出处
《物流科技》
2025年第2期161-165,共5页
Logistics Sci Tech
基金
中国物流学会、中国物流与采购联合会研究课题“基于实时信息的冷链物流配送路径研究”(2022CSLKT3-022)。
关键词
碳排放
冷链物流
路径优化
遗传算法
carbon emission
cold chain logistics
path optimization
genetic algorithm
