低碳目标下改进聚类算法的生鲜前置仓选址研究

Research on Pre-Warehouse Location of Fresh Food Based on Improved Clustering Algorithm Under Low Carbon Target

2020年我国在联合国大会上提出双碳目标,各行业节能减排的力度都在不断加大。近年来涌现的生鲜前置仓模式在为人们带来便利的同时也产生了大量碳排放,因此在选址布局研究中需要将碳排放作为重要因素考虑进去。以生鲜前置仓为研究对象,首先通过计算配送产生的碳排放量,以碳排放最小化为目标改进K-means聚类算法来选取前置仓备选点,再从降低成本和提高配送效率的角度建立目标规划模型,合理规划前置仓和需求点的布局。最后以北京市城市副中心美团买菜为例进行实证分析,在预测需求量的基础上划分出36个需求点,通过求解构建的优化模型得到该区域前置仓的最佳布局,最终得到碳排放最小化和低成本高效率的最优选址布局方案,实现经济和环保双赢。

Since China proposed the dual carbon target at the United Nations General Assembly in 2020, all industries have made efforts in energy conservation and emission reduction. In recent years, the emergence of a pre-warehouse mode of fresh food has brought convenience to people and produced a lot of carbon emissions. Therefore, carbon emissions, as an important factor, shall be taken into account in the study on location and layout. This paper took the pre-warehouse of fresh food as the research object. Firstly, the carbon emissions generated by distribution were calculated, and the K-means clustering algorithm was improved to select alternative sites for the pre-warehouse, with the goal of minimizing carbon emissions. Then the objective programming model was established in terms of reducing cost and improving distribution efficiency, so as to reasonably plan the layout of pre-warehouses and sites in demand. This paper took Meituanmaicai in Beijing sub-center as an example for empirical analysis and divided 36 sites in demand according to the predicted demand. By solving the optimization model constructed in this paper, the optimal layout of the pre-warehouse in this area was obtained. Finally, the optimal location and layout scheme with minimum carbon emissions, low cost, and high efficiency was obtained to achieve a win-win situation for the economy and environmental protection.