摘要
为提高可回收物收运效率,优化设施空间布局,研究基于K-means聚类算法,提出了三种改进方法:引入实际路网距离替代欧式距离、赋予交投点人口分布权重以及优化交投点服务均衡性。据此建立了3种改进K-means聚类算法的可回收物中转站选址模型,并采用方差比和分布均衡度指标评估聚类选址效果。以北京市朝阳区为例的实证研究结果显示,所有算法均有效实现了该区可回收物中转站的布局优化,使各中转站具有适当的服务半径。四种中转站选址布局策略,分布方差比分别为6.5329、7.2047、6.4114、10.6215,分布均衡度分别为1.0201、1.0169、1.7211、1.8672;其中基于9个中转站的选址策略体现出最佳的服务均衡性和空间覆盖效率。
To enhance the efficiency of recyclable waste collection and transportation and optimize the spatial layout of facilities,three improved methods were proposed in this study based on the K-means clustering algorithm:replacing Euclidean distance with actual road network distance,assigning population distribution weights to collection points,and optimizing the service balance of collection points.Accordingly,three improved K-means clustering models for the location selection of recyclable waste transfer stations were established,and the effectiveness of clustering-based site selection was evaluated by using variance ratio and distribution balance metrics.An empirical study conducted in Chaoyang District,Beijing,demonstrated that all algorithms effectively optimized the layout of recyclable waste transfer stations in the district,ensuring appropriate service radiifor each station.The four site layout strategies for transfer stations yielded variance ratios of 6.5329,7.2047,6.4114,and 10.6215,and distribution balance metrics of 1.0201,1.0169,1.7211,and 1.8672,respectively.Among these,the strategy based on nine transfer stations exhibited the best service balance and spatial coverage efficiency.
作者
朱远超
王晓燕
王超
ZHU Yuan-chao;WANG Xiao-yan;WANG Chao(Beijing Municipal Institute of City Management,Beijing 100028,China;College of Economics and Management,Beijing University of Technology,Beijing 100124,China)
出处
《四川环境》
2025年第5期119-127,共9页
Sichuan Environment
关键词
可回收物
中转站
K-MEANS聚类算法
设施选址优化
Recyclable waste
transfer station
K-means clustering algorithm
facility location optimization
