摘要
为了解决生鲜电商在选址过程中忽视碳排放量的不足之处,以生鲜电商前置仓为例,在充分考虑前置仓选址的约束问题前提下,根据货损成本、改造成本、运营成本、制冷成本以及处理低碳排放成本,构建一个以最小总成本为目标的选址模型,并针对模型的特征选取对应的编码方式、交叉和变异算子,设计遗传算法对模型进行求解。算例结果进一步证明了该模型与算法的有效性,并为碳交易环境下生鲜电商物流设施节点选址提供了有益借鉴。
With the official establishment of my country's carbon emissions trading market,in order to solve the shortcomings of fresh food e-commerce ignoring carbon emissions in the site selection process,take the fresh food e-commerce front warehouse as an example,and fully consider the location of the front warehouse.Under the premise of the constraint problem,according to the cost of cargo damage,renovation cost,operating cost,cooling cost and processing low carbon emission cost,construct a site selection model with the minimum total cost as the goal,and select the corresponding coding method according to the characteristics of the model,crossover and mutation operators,genetic algorithm is designed to solve the model.The results of the calculation example further prove the effectiveness of the model and algorithm,and provide a useful reference for the construction of fresh food e-commerce logistics facility node location in the carbon trading environment.
作者
朱铃
杨中华
车路涛
ZHU Ling;YANG Zhonghua;CHE Lutao(School of Evergrande Management,Wuhan University of Science&Technology,Wuhan 430065,China;Center for Service Science and Engineering,Wuhan University of Science&Technology,Wuhan 430065,China;Hubei Province Center for Industrial Policy and Management Research,Wuhan 430065,China)
出处
《物流科技》
2022年第4期44-49,共6页
Logistics Sci-Tech
基金
湖北省教育厅科学研究中青年人才项目(Q20171112)
湖北省教育厅人文社会科学重点研究项目(17D009)。
关键词
碳交易
前置仓
选址
遗传算法
carbon trading
front warehouse
location selection
genetic algorithm