結果
問題 | No.5007 Steiner Space Travel |
ユーザー | Kiri8128 |
提出日時 | 2022-07-30 16:44:10 |
言語 | PyPy3 (7.3.15) |
結果 |
AC
|
実行時間 | 899 ms / 1,000 ms |
コード長 | 9,527 bytes |
コンパイル時間 | 409 ms |
実行使用メモリ | 89,164 KB |
スコア | 5,670,800 |
最終ジャッジ日時 | 2022-07-30 16:44:41 |
合計ジャッジ時間 | 30,178 ms |
ジャッジサーバーID (参考情報) |
judge14 / judge10 |
純コード判定しない問題か言語 |
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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 | 887 ms
88,280 KB |
testcase_01 | AC | 888 ms
86,308 KB |
testcase_02 | AC | 897 ms
86,164 KB |
testcase_03 | AC | 887 ms
85,852 KB |
testcase_04 | AC | 887 ms
86,520 KB |
testcase_05 | AC | 886 ms
85,560 KB |
testcase_06 | AC | 887 ms
87,532 KB |
testcase_07 | AC | 886 ms
85,904 KB |
testcase_08 | AC | 886 ms
87,328 KB |
testcase_09 | AC | 898 ms
86,700 KB |
testcase_10 | AC | 889 ms
87,976 KB |
testcase_11 | AC | 887 ms
87,552 KB |
testcase_12 | AC | 888 ms
86,424 KB |
testcase_13 | AC | 891 ms
85,632 KB |
testcase_14 | AC | 889 ms
87,600 KB |
testcase_15 | AC | 886 ms
88,280 KB |
testcase_16 | AC | 899 ms
89,164 KB |
testcase_17 | AC | 886 ms
87,392 KB |
testcase_18 | AC | 888 ms
86,256 KB |
testcase_19 | AC | 889 ms
85,264 KB |
testcase_20 | AC | 887 ms
86,368 KB |
testcase_21 | AC | 887 ms
86,040 KB |
testcase_22 | AC | 887 ms
86,332 KB |
testcase_23 | AC | 896 ms
85,876 KB |
testcase_24 | AC | 886 ms
86,016 KB |
testcase_25 | AC | 889 ms
88,892 KB |
testcase_26 | AC | 885 ms
85,976 KB |
testcase_27 | AC | 892 ms
86,900 KB |
testcase_28 | AC | 890 ms
87,776 KB |
testcase_29 | AC | 884 ms
87,236 KB |
ソースコード
from time import time from math import exp key = 3 rnd_mod = 12345678901234567891 rnd_x = 9876543210987654321 + 1234567890123456789 * key % rnd_mod def rnd(): global rnd_x rnd_x = rnd_x**2 % rnd_mod return (rnd_x>>10) % (1<<40) def Randrange(a, b=-1): if b > 0: return Randrange(b-a) + a return rnd() % a def Random(): return Randrange(10 ** 9) / (10 ** 9) LOCAL = 0 if LOCAL: N, M = 100, 8 X = [(477, 514), (703, 786), (577, 572), (327, 487), (951, 516), (782, 153), (423, 656), (341, 549), (754, 45), (317, 592), (588, 809), (644, 212), (451, 345), (716, 164), (497, 469), (391, 287), (618, 266), (26, 823), (637, 896), (688, 549), (566, 337), (826, 239), (145, 711), (28, 842), (715, 744), (714, 318), (758, 619), (727, 621), (533, 162), (385, 510), (336, 570), (794, 449), (510, 297), (110, 735), (767, 199), (619, 759), (563, 934), (822, 469), (645, 160), (154, 696), (580, 315), (788, 431), (164, 693), (315, 598), (568, 538), (802, 587), (863, 314), (776, 382), (408, 398), (421, 516), (445, 931), (180, 673), (540, 640), (711, 706), (702, 132), (560, 849), (849, 534), (363, 608), (914, 550), (413, 460), (526, 972), (436, 608), (807, 469), (517, 430), (699, 191), (755, 440), (192, 680), (329, 669), (22, 793), (314, 564), (505, 688), (579, 899), (746, 727), (820, 722), (495, 510), (611, 883), (171, 838), (441, 639), (715, 707), (843, 324), (643, 689), (736, 456), (527, 582), (383, 593), (173, 655), (823, 428), (867, 203), (183, 810), (468, 333), (514, 821), (727, 356), (847, 655), (578, 519), (638, 794), (866, 292), (695, 69), (987, 620), (961, 610), (844, 399), (811, 678)] else: N, M = map(int, input().split()) X = [] for _ in range(N): a, b = map(int, input().split()) X.append((a, b)) alpha = 5 alpha2 = alpha ** 2 class State(): def __init__(self, order, station_positions): self.order = order self.station_positions = station_positions def calc_energy(self): self.pre_calc() sum_energy = 0 for i, j in zip(self.order, self.order[1:]): sum_energy += self.energy_between(i, j) return sum_energy def calc_best_move(self): self.pre_calc_hist() L = [(1, 0)] for i, j in zip(self.order, self.order[1:]): L += self.best_move_between(i, j) return L def nearest(self, i): mim = -1 x, y = X[i] s = 10 ** 9 for m, (xx, yy) in enumerate(self.station_positions): t = (x - xx) ** 2 + (y - yy) ** 2 if t < s: s = t mim = m return mim # , s * alpha def energy_between(self, i, j): # energy from planet i to planet j x1, y1 = X[i] x2, y2 = X[j] ii = self.nearest(i) jj = self.nearest(j) x3, y3 = self.station_positions[ii] x4, y4 = self.station_positions[jj] # i -> j s = ((x1 - x2) ** 2 + (y1 - y2) ** 2) * alpha2 # i -> ii -> j t = ((x1 - x3) ** 2 + (y1 - y3) ** 2) * alpha + ((x2 - x3) ** 2 + (y2 - y3) ** 2) * alpha if t < s: s = t # i -> jj -> j t = ((x1 - x4) ** 2 + (y1 - y4) ** 2) * alpha + ((x2 - x4) ** 2 + (y2 - y4) ** 2) * alpha if t < s: s = t # i -> ii > jj -> j t = ((x1 - x3) ** 2 + (y1 - y3) ** 2) * alpha + ((x2 - x4) ** 2 + (y2 - y4) ** 2) * alpha t += self.dist_between_stations[ii][jj] if t < s: s = t return s def best_move_between(self, i, j): x1, y1 = X[i] x2, y2 = X[j] ii = self.nearest(i) jj = self.nearest(j) x3, y3 = self.station_positions[ii] x4, y4 = self.station_positions[jj] # i -> j s = ((x1 - x2) ** 2 + (y1 - y2) ** 2) * alpha2 L = [(1, j)] # i -> ii -> j t = ((x1 - x3) ** 2 + (y1 - y3) ** 2) * alpha + ((x2 - x3) ** 2 + (y2 - y3) ** 2) * alpha if t < s: s = t L = [(2, ii), (1, j)] # i -> jj -> j t = ((x1 - x4) ** 2 + (y1 - y4) ** 2) * alpha + ((x2 - x4) ** 2 + (y2 - y4) ** 2) * alpha if t < s: s = t L = [(2, jj), (1, j)] # i -> ii > jj -> j t = ((x1 - x3) ** 2 + (y1 - y3) ** 2) * alpha + ((x2 - x4) ** 2 + (y2 - y4) ** 2) * alpha t += self.dist_between_stations[ii][jj] if t < s: s = t L = [(2, ii), (2, jj), (1, j)] return L def pre_calc(self): dist_between_stations = [[0] * M for _ in range(M)] for i in range(M): x1, y1 = station_positions[i] for j in range(i): x2, y2 = station_positions[j] s = (x1 - x2) ** 2 + (y1 - y2) ** 2 if 1: for k in range(M): if i == k or j == k: continue x3, y3 = station_positions[k] t = (x1 - x3) ** 2 + (y1 - y3) ** 2 + (x2 - x3) ** 2 + (y2 - y3) ** 2 s = min(s, t) dist_between_stations[i][j] = s dist_between_stations[j][i] = s self.dist_between_stations = dist_between_stations def pre_calc_hist(self): dist_between_stations = [[0] * M for _ in range(M)] hist_between_stations = [[-1] * M for _ in range(M)] for i in range(M): x1, y1 = station_positions[i] for j in range(i): x2, y2 = station_positions[j] s = (x1 - x2) ** 2 + (y1 - y2) ** 2 best_h = -1 for k in range(M): if i == k or j == k: continue x3, y3 = station_positions[k] t = (x1 - x3) ** 2 + (y1 - y3) ** 2 + (x2 - x3) ** 2 + (y2 - y3) ** 2 if t < s: s = t best_h = k dist_between_stations[i][j] = s dist_between_stations[j][i] = s hist_between_stations[i][j] = best_h hist_between_stations[j][i] = best_h self.dist_between_stations = dist_between_stations self.hist_between_stations = hist_between_stations order = [i for i in range(100)] + [0] station_positions = [(500, 100 * (i + 1)) for i in range(8)] state = State(order, station_positions) energy = state.calc_energy() best_energy = 10 ** 18 sTime = time() time_limit = 3 if not LOCAL: time_limit = 0.8 T_start = 1000000 T_end = 10000 while 1: progress = ((time() - sTime) / time_limit) if progress >= 1: break T = T_start * (T_end / T_start) ** progress if progress < 0: tp = 0 else: tp = Randrange(-2, 3) if tp <= 0: i, j = 0, 0 while i == j: i = Randrange(1, N) j = Randrange(1, N) if i > j: i, j = j, i n_order = order[:i] + order[i:j][::-1] + order[j:] n_state = State(n_order, station_positions) n_energy = n_state.calc_energy() if n_energy <= energy or Random() < exp(-min((n_energy - energy) / T, 100)): order = n_order state = n_state energy = n_energy if LOCAL: print("Type0", energy, int(10 ** 9 / (energy ** 0.5 + 1000) + 0.5), time() - sTime, "T =", T) elif tp == 2: m = Randrange(M) nx, ny = Randrange(50, 951), Randrange(50, 951) n_station_positions = station_positions[:] n_station_positions[m] = (nx, ny) n_state = State(order, n_station_positions) n_energy = n_state.calc_energy() if n_energy <= energy or Random() < exp(-min((n_energy - energy) / T, 100)): station_positions = n_station_positions state = n_state energy = n_energy if LOCAL: print("Type1", energy, int(10 ** 9 / (energy ** 0.5 + 1000) + 0.5), time() - sTime, "T =", T) elif tp == 1: m = Randrange(M) x, y = station_positions[m] dx, dy = Randrange(-50, 51), Randrange(-50, 51) nx = min(max(x + dx, 0), 1000) ny = min(max(y + dy, 0), 1000) n_station_positions = station_positions[:] n_station_positions[m] = (nx, ny) n_state = State(order, n_station_positions) n_energy = n_state.calc_energy() if n_energy <= energy or Random() < exp(-min((n_energy - energy) / T, 100)): station_positions = n_station_positions state = n_state energy = n_energy if LOCAL: print("Type2", energy, int(10 ** 9 / (energy ** 0.5 + 1000) + 0.5), time() - sTime, "T =", T) else: assert 0 if energy < best_energy: best_energy = energy best_state = state best_order = order[:] best_station_positions = station_positions[:] best_score = int(10 ** 9 / (best_energy ** 0.5 + 1000) + 0.5) if LOCAL: print("★ tp =", max(tp, 0), "score =", best_score) if LOCAL: print("best_energy, best_score =", best_energy, best_score) print("-" * 50) print() for x, y in best_station_positions: print(x, y) b = best_state.calc_best_move() print(len(b)) for t, i in b: print(t, i + 1)