import sys
import random
import time
import math

from a import TSP
from kmeans import KmeansPlusPlus


N, M = map(int, input().split())
AB = [tuple(map(int, input().split())) for _ in range(N)]

kmeans = KmeansPlusPlus(M)
labels, cluster_centers = kmeans.fit(AB)

obj = AB + cluster_centers

dist = [[0]*(N+M) for _ in range(N+M)]
for i in range(N+M):
  for j in range(N+M):
    d = (obj[i][0] - obj[j][0])**2 + (obj[i][1] - obj[j][1])**2
    if i < N:
      d *= 5
    if j < N:
      d *= 5
    dist[i][j] = 5

tsp = TSP(obj)
path, score, loops = tsp.solve()
print(score, file=sys.stderr)

for c,d in cluster_centers:
  print(c, d)
print(len(path))
for p in path:
  if p < N:
    print(1, p+1)
  else:
    print(2, p-N+1)