update

R/greedy/TSP.R

@@ -1,69 +1,96 @@
-"""
-Name: Shuoyi Yang
-UTEID: sy6955
 
-CS 345
-Greed algorithm for TSP.
-
-"""
-
-#reading from the input path
-filepath = "a280.tsp"
-data = read.table(filepath,skip =6, header=FALSE,nrow=length(readLines(filepath))-7)
-
-
-#calculate the euclidean distance between two node
-distance <- function(x1,x2){
-	return (sqrt(sum((x1-x2)^2)))
-}
-
-
-#find the nearest node from the remaining list
-get.nearest<- function(remain.nodes,current){
-	i = 0
-	shortest.dist = 0
-	min  = c()
-	current=current[2:3]
-	rec = numeric(nrow(remain.nodes))
-	id = remain.nodes[,1]
-	cor = remain.nodes[,2:3]
-	for(i in 1:nrow(remain.nodes)){
-		#store the distance of nodes into a vector
-		cur.dist = distance(current,cor[i,])
-		min = rbind(min,c(i,id[i],cur.dist))
+#Name: Shuoyi Yang
+#UTEID: sy6955
+
+#CS 345
+#Greed algorithm for TSP.
+
+
+	#reading data from the input path
+	read.data<-function(){
+	filepath = readline("Enter data file:")	
+	data = read.table(filepath,skip =6, header=FALSE,nrow=length(readLines(filepath))-7)
+	return(data)
 	}
-	min.node = min[which.min(min[,3]),]
-	return (min.node)
-}
-
-
-#get the list of nodeId and minimum distance by greedy algorithm
-min.total.dist = 0
-best.result = c()
-for (i in 1:nrow(data)){
-	total.dist = 0
-	visit.nodes = c()
-	current = data[i,]
-	visit.nodes = current
-	#remain.nodes = subset(data,V1!=i)
-	remain.nodes = data[-i,]
 
-	while(nrow(remain.nodes)>0) {
-		current = tail(visit.nodes,n=1)		
-		next.node = get.nearest(remain.nodes,current) 
-		visit.nodes = rbind(visit.nodes,data[next.node[2],])			
-		#remain.nodes = subset(remain.nodes,V1!=next.node[1])
-		remain.nodes = remain.nodes[-next.node[1],]
-		total.dist = total.dist + next.node[3]
+	#calculate the euclidean distance between two node
+	distance <- function(x1,x2){
+		return (sqrt(sum((x1-x2)^2)))
 	}
 
-	if(total.dist < min.total.dist){
-		min.total.dist = total.dist
-		best.result = remain.nodes[,1]
+
+	#find the nearest node from the remaining list
+	get.nearest<- function(remain.nodes,current){
+		i = 0
+		shortest.dist = 0
+		min  = c()
+		current=current[2:3]
+		rec = numeric(nrow(remain.nodes))
+		id = remain.nodes[,1]
+		cor = remain.nodes[,2:3]
+		for(i in 1:nrow(remain.nodes)){
+			#store the distance of nodes into a vector
+			cur.dist = distance(current,cor[i,])
+			min = rbind(min,c(i,id[i],cur.dist))
+		}
+		min.node = min[which.min(min[,3]),]
+		return (min.node)
 	}
-
-}
-
-print(min.total.dist)
-print(best.result)
-
+
+
+	#get the list of nodeId and minimum distance by greedy algorithm
+
+
+	#find the shortest path for any start point
+	any.start.shortest.path<-function(data){
+	min.total.dist = 0
+	best.result = c()
+	for (i in 1:nrow(data)){
+		total.dist = 0
+		visit.nodes = c()
+		current = data[i,]
+		visit.nodes = current
+		#remain.nodes = subset(data,V1!=i)
+		remain.nodes = data[-i,]
+
+		while(nrow(remain.nodes)>0) {
+			current = tail(visit.nodes,n=1)		
+			next.node = get.nearest(remain.nodes,current) 
+			visit.nodes = rbind(visit.nodes,data[next.node[2],])			
+			remain.nodes = remain.nodes[-next.node[1],]
+			total.dist = total.dist + next.node[3]
+			}
+		if(total.dist < min.total.dist){
+			min.total.dist = total.dist
+			best.result = visit.nodes[,1]
+			}
+		}
+		print(paste("minimum distance:",min.total.dist))
+		print(best.result)
+	}
+
+	#find the shortest path from node 1
+	shortest.path<-function(data){
+		first.node = data[1,]
+		remain.nodes = data[-1,]
+		total.dist = 0
+		visit.nodes=first.node
+			while(nrow(remain.nodes)>0) {
+			current = tail(visit.nodes,n=1)		
+			next.node = get.nearest(remain.nodes,current) 
+			visit.nodes = rbind(visit.nodes,data[next.node[2],])			
+			remain.nodes = remain.nodes[-next.node[1],]
+			total.dist = total.dist + next.node[3]
+			}
+		print(paste("minimum distance :",total.dist))
+		print(visit.nodes[,1])
+	}
+
+	#main function
+	main<-function(){
+	shortest.path(read.data())
+	#any.start.shortest.path(read.data())
+	}
+
+
+   if(interactive()) main()