R中利用聚类计算最优路径的有效方法
我有一个集群坐标数据集，希望能够计算每个集群内的最佳路径。我不关心以任何方式对集群进行排序（因此这与多个销售人员的旅行销售人员问题不同），我只关心每个集群内的路径是最有效的路径。以下是我正在处理的一些虚拟数据：R中利用聚类计算最优路径的有效方法,r,cluster-analysis,distance,R,Cluster Analysis,Distance,我有一个集群坐标数据集，希望能够计算每个集群内的最佳路径。我不关心以任何方式对集群进行排序（因此这与多个销售人员的旅行销售人员问题不同），我只关心每个集群内的路径是最有效的路径。以下是我正在处理的一些虚拟数据： text <- ("block_id y_cent x_cent 1 0 86.32583 21.23006 2 0 86.34592 21.26965 3 0
text <- ("block_id y_cent x_cent
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df <- read.table(text = text, header = T, fill = T)
text使用R中的TSP包快速解决此问题的方法：
按块/簇变量对数据进行分组：
df <- dplyr::group_by(df, block_id)
使用R中的TSP包快速解决此问题的方法：
按块/簇变量对数据进行分组：
df <- dplyr::group_by(df, block_id)
all_block_paths_list <- list()
for(i in 1:length(df_by_block)){
# calculate optimum path
tsp <- TSP::TSP(dist(df_by_block[[i]][,c("x_cent", "y_cent")]))
tsp <- TSP::insert_dummy(tsp, label = "cut")
initial_tour <- TSP::solve_TSP(tsp)
tour <- TSP::solve_TSP(tsp, model = "two_opt", control = list(tour = initial_tour))
path.tsp <- unname(TSP::cut_tour(tour, "cut"))
# Save new datasets in list
all_block_paths_list[[i]] <- df_by_block[[i]][path.tsp,]
}
all_block_paths_df <- dplyr::bind_rows(all_block_paths_list)
library(ggplot2)
ggplot() +
geom_point(all_block_paths_df, mapping = aes(x = x_cent, y = y_cent, color = factor(block_id)), size = 2) +
geom_path(all_block_paths_df, mapping = aes(x = x_cent, y = y_cent, color = factor(block_id))) +
labs(title = "Optimum path distance within clusters",
x = "",
y = "") +
theme_bw() +
theme(title = element_text(size = 16),
legend.position = "none")