碳税政策下基于BFA-ACO的冷链物流路径优化  

Cold Chain Logistics Path Optimization Based on BFA-ACO Under Carbon Tax Policy

作　　者：张天瑞[1] 刘海波 ZHANG Tianrui;LIU Haibo(School of Mechanical Engineering,Shenyang University,Shenyang 110044,China)

机构地区：[1]沈阳大学机械工程学院,辽宁沈阳110044

出　　处：《沈阳大学学报（自然科学版）》2022年第5期363-372,共10页Journal of Shenyang University：Natural Science

基　　金：中央引导地方科技发展资金计划项目(2021JH6/10500149)。

摘　　要：针对2020年新冠肺炎疫情期间冷链物流市场的特点以及碳税政策的开展,引入消毒成本和碳税成本,充分分析了消毒成本与货损成本以及时间惩罚成本之间的关系,以总成本最低为优化目标建立了冷链物流路径优化模型。进而通过分析细菌觅食算法(BFA)和蚁群算法(ACO)的优缺点,将二者相结合建立BFA-ACO混合算法,在蚁群算法中引入细菌觅食算法的复制和趋化操作,以提高算法的收敛速度和全局收敛能力。再利用该混合算法对冷链物流路径优化模型进行优化求解,与求解冷链物流经典算法GA、ABC和ACO进行比较。对比优化结果发现:通过细菌觅食-蚁群算法对模型进行优化的效果优于单一算法对模型进行优化的效果。According to the characteristics of cold chain logistics market during the COVID-19 period in 2020 and the development of carbon tax policy,the disinfection cost and carbon tax cost were introduced,and the relationship between disinfection cost,cargo damage cost and time penalty cost was fully analyzed.Taking the minimum total cost as the objective,the cold chain optimization model was established,the advantages and disadvantages of BFA algorithm and ant colony algorithm were analyzed,and the cold chain optimization model was given bacterial foraging algorithm.Then,the hybrid algorithm was used to optimize the cold chain logistics path optimization model.The comparison of the optimization results shows that the optimization effect of bacterial foraging and ant colony algorithm on the model is better than that of the single algorithm.

关 键 词：冷链物流 路径优化 碳税 消毒成本 细菌觅食-蚁群算法 

分 类 号：F252.5[经济管理—国民经济]