基于K-Means算法和重心法求解多配送中心选址问题

Solving Multiple Distribution Center Location Allocation Problem Using K-Means Algorithm and Center of Gravity Method

分析了P-中值模型的特点,阐述了传统的模型与算法在求解大量需求点选择问题的局限性,提出了利用改进K-Means算法和重心法相结合的方式来求解该问题的思路,并提出以噪音率来刻画选址的效果,利用公开的数据设计了数值实验,证明该算法是收敛且实用的。

This paper analyzes the characteristics of the P-median model, expounds the limitations of traditional models and algorithms in solving selection problems involving a large number of demand points, puts forward the idea of combining the improved K- Means algorithm with the center of gravity method to solve such problems, and proposes to use noise rate to characterize the effect of site selection. Next, it designs a numerical experiment using public data and proves that the algorithm is convergent and practical.