Open AccessSolving Multiple Distribution Center Location Allocation Problem Using K-Means Algorithm and Center of Gravity Method Take Jinjiang District of Chengdu as an example
Author(s) -
Chunling Cai,
Yong Luo,
Yuehong Cui,
Feng Chen
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/587/1/012120
Subject(s) - center of gravity , center (category theory) , distribution center , cluster analysis , facility location problem , algorithm , computer science , location model , value (mathematics) , logistics center , location allocation , distribution (mathematics) , mathematical optimization , mathematics , operations research , artificial intelligence , economics , management , mathematical analysis , chemistry , commerce , machine learning , crystallography
In the logistics system, logistics nodes play an important role. The centre-of-gravity method is one of the most basic methods in solving the problem of single facility location. The thesis first uses the K-means clustering algorithm to divide the demand points into k clusters, and the k value is selected by the elbow method. Then, the k clusters are regarded as a single facility location problem and analyzed by the center of gravity method. In practical applications, the discrete model analysis can be cited to further obtain the optimal solution.