結果
問題 | No.5007 Steiner Space Travel |
ユーザー | brthyyjp |
提出日時 | 2023-04-25 18:26:04 |
言語 | PyPy3 (7.3.15) |
結果 |
TLE
|
実行時間 | - |
コード長 | 4,560 bytes |
コンパイル時間 | 464 ms |
コンパイル使用メモリ | 87,164 KB |
実行使用メモリ | 79,604 KB |
スコア | 7,752,845 |
最終ジャッジ日時 | 2023-04-25 18:26:40 |
合計ジャッジ時間 | 33,808 ms |
ジャッジサーバーID (参考情報) |
judge14 / judge11 |
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テストケース
テストケース表示入力 | 結果 | 実行時間 実行使用メモリ |
---|---|---|
testcase_00 | AC | 994 ms
79,436 KB |
testcase_01 | AC | 993 ms
79,276 KB |
testcase_02 | TLE | - |
testcase_03 | AC | 994 ms
79,180 KB |
testcase_04 | AC | 994 ms
79,432 KB |
testcase_05 | AC | 995 ms
79,300 KB |
testcase_06 | AC | 994 ms
79,080 KB |
testcase_07 | AC | 994 ms
79,112 KB |
testcase_08 | AC | 997 ms
79,440 KB |
testcase_09 | AC | 995 ms
79,472 KB |
testcase_10 | AC | 996 ms
79,432 KB |
testcase_11 | AC | 994 ms
79,440 KB |
testcase_12 | AC | 995 ms
79,352 KB |
testcase_13 | AC | 994 ms
79,320 KB |
testcase_14 | AC | 995 ms
79,172 KB |
testcase_15 | AC | 994 ms
79,432 KB |
testcase_16 | AC | 994 ms
79,344 KB |
testcase_17 | AC | 994 ms
79,416 KB |
testcase_18 | AC | 995 ms
79,312 KB |
testcase_19 | AC | 994 ms
79,304 KB |
testcase_20 | AC | 999 ms
79,352 KB |
testcase_21 | AC | 995 ms
79,200 KB |
testcase_22 | AC | 995 ms
79,436 KB |
testcase_23 | AC | 993 ms
79,176 KB |
testcase_24 | AC | 994 ms
79,260 KB |
testcase_25 | AC | 995 ms
79,096 KB |
testcase_26 | AC | 995 ms
79,604 KB |
testcase_27 | AC | 996 ms
79,568 KB |
testcase_28 | AC | 994 ms
79,268 KB |
testcase_29 | AC | 994 ms
79,516 KB |
ソースコード
import math import random import os import io import sys from time import time start_time = time() input = sys.stdin.readline random.seed(42) alpha = 5 mx = 1000 INF = float('inf') Ts = 50 Te = 10 TIME_LIMIT = 0.9 TIME_LIMIT_INS = 0.9 max_iter = 50 limit = 700 n, m = map(int, input().split()) XY = [] for i in range(n): x, y = map(int, input().split()) XY.append((x, y)) def kMeans(XY, k): n = len(XY) clusters = [random.randint(0, k-1) for i in range(n)] for _ in range(max_iter): centroidX = [0]*k centroidY = [0]*k clusterCnt = [0]*k for i, c in enumerate(clusters): clusterCnt[c] += 1 centroidX[c] += XY[i][0] centroidY[c] += XY[i][1] for c in range(k): if clusterCnt[c] == 0: centroidX[c] = random.randint(0, mx) centroidY[c] = random.randint(0, mx) else: centroidX[c] //= clusterCnt[c] centroidY[c] //= clusterCnt[c] newClusters = [-1]*n for i in range(n): mn = INF nc = -1 x, y = XY[i] for c in range(k): d = (x-centroidX[c])**2+(y-centroidY[c])**2 if d < mn: mn = d nc = c newClusters[i] = nc clusters = newClusters return centroidX, centroidY CD = [] centroidX, centroidY = kMeans(XY, m) for c, d in zip(centroidX, centroidY): CD.append((c, d)) XY += CD def calc_energy(i, j): xi, yi = XY[i] xj, yj = XY[j] d2 = (xi-xj)**2+(yi-yj)**2 if 0 <= i < n and 0 <= j < n: return (alpha**2)*d2 elif n <= i < n+m and n <= j < n+m: return d2 else: return alpha*d2 g = [[] for i in range(n+m)] dist_table = [[INF]*(n+m) for i in range(n+m)] for i in range(n+m): for j in range(n+m): if i == j: continue x1, y1 = XY[j] dist = calc_energy(i, j) g[i].append((dist, j)) dist_table[i][j] = dist def calc_dist(path, dist_table): res = 0 for v, nv in zip(path, path[1:]): res += dist_table[v][nv] return res def nearest_neighbor(s, g): n = len(g) nonvisit = set(range(n)) path = [] path.append(s) nonvisit.remove(s) while nonvisit: min_dist = INF nx = -1 for d, v in g[path[-1]]: if not v in nonvisit: continue if d < min_dist: min_dist = d nx = v path.append(nx) nonvisit.remove(nx) return path+[s] def insert_station(path, dist_table, time_limit): while True: now_time = time() if now_time - start_time > time_limit: return path i = random.randint(0, len(path)-2) u, v = path[i], path[i+1] min_dist = dist_table[u][v] nx = -1 for k in range(m): w = n+k temp = dist_table[u][w]+dist_table[w][v] if temp <= min_dist: min_dist = temp nx = w if nx != -1: path = path[0:i+1]+[nx]+path[i+1:] return path def two_opt_with_annealing(path, dist_table, Ts, Te, time_limit): n = len(path) while True: now_time = time() if now_time - start_time > time_limit: return path for i in range(n-3): p1 = path[i] p2 = path[i+1] p_dist = dist_table[p1][p2] for j in range(i+2, n-1): q1 = path[j] q2 = path[j+1] q_dist = dist_table[q1][q2] cur_dist = p_dist + q_dist new_dist = dist_table[p1][q1]+dist_table[p2][q2] diff = new_dist-cur_dist temp = Ts+(Te-Ts)*(time()-start_time)/time_limit prob = math.exp(min(limit, -diff / temp)) if prob > random.random(): sep1, sep2, sep3 = path[:i+1], path[i+1:j+1], path[j+1:] sep2.reverse() path = sep1+sep2+sep3 path = nearest_neighbor(0, g) path = insert_station(path, dist_table, TIME_LIMIT_INS) #path = two_opt_with_annealing(path, dist_table, Ts, Te, TIME_LIMIT) s = calc_dist(path, dist_table) score = round(10**9/(1000+math.sqrt(s))) print(score, file=sys.stderr, flush=True) for c, d in CD: print(c, d) print(len(path)) for k in range(len(path)): r = path[k] if 0 <= r < n: print(1, r+1) else: print(2, r-n+1)