摘要
考虑B2B电商环境下随机需求以及低碳要求对物流配送环节的影响,以配送总成本最小、车队规模最小以及客户时间满意度最大为目标,建立基于低碳与随机需求的多目标模型,针对该模型特点,设计基于Pareto最优的多目标遗传算法。最后以步步高集团云通物流为实际配送优化案例,对上述优化模型及其求解算法的有效性进行验证。研究结果表明:从政府管理的角度,碳税额定为70元/t最优,从物流配送行业的角度,碳税额定为40元/t最优。配送企业的不同优化目标偏好与配送优化决策方案的选择密切相关。本模型可为政府制定合理的碳税政策以及企业制定合理的配送决策提供理论依据。
A multi-objective model based on low-carbon and random demand was established,with the impact of random demand and low-carbon factors on distribution under B2B e-commerce environmentconsidered.The objectives of the proposed model were(i)to reduce total distribution cost,(ii)to minimize the fleet size,and(iii)to maximizecustomers’time satisfaction.A multi-objective genetic algorithm based on Pareto optimal solution was proposed to achieve these objectives.A real case of Yuntong logistics company was implemented to verify the optimization model and its algorithm.From the perspective of government management,carbon tax was set at 70 yuan/ton,and from the perspective of logistics distribution industry,carbon tax was set at 40 yuan/ton.The preference of different optimization goals of distribution enterprises was related to the choice of distribution optimization decision scheme.The models may provide theoretical bases for the government to make reasonable low-carbon policies,and for the enterprises to make reasonable distribution decisions.
作者
张得志
乔馨
肖博文
王日东
毛成辉
ZHANG Dezhi;QIAO Xin;XIAO Bowen;WANG Ridong;MAO Chenghui(Traffic&Transportation Engineering,Central South University,Changsha 410075,China;School of Mechanical Engineering,Tsinghua University,Beijing 100084,China)
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2021年第8期2165-2174,共10页
Journal of Railway Science and Engineering
基金
国家自然科学基金资助项目(71672193)
“先进轨道交通”专项国家重点研发计划资助项目(2017YFB1201304)。
关键词
低碳物流
车辆路径
遗传算法
多目标优化
low-carbon logistics
vehicle routing problem
genetic algorithm
multi-objective optimization
