結果
問題 | No.134 走れ!サブロー君 |
ユーザー | Ueki |
提出日時 | 2019-05-16 12:40:55 |
言語 | Python3 (3.12.2 + numpy 1.26.4 + scipy 1.12.0) |
結果 |
AC
|
実行時間 | 1,431 ms / 5,000 ms |
コード長 | 1,762 bytes |
コンパイル時間 | 101 ms |
コンパイル使用メモリ | 12,120 KB |
実行使用メモリ | 13,540 KB |
最終ジャッジ日時 | 2023-10-17 06:50:45 |
合計ジャッジ時間 | 5,384 ms |
ジャッジサーバーID (参考情報) |
judge12 / judge13 |
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 | 30 ms
10,248 KB |
testcase_01 | AC | 29 ms
10,248 KB |
testcase_02 | AC | 30 ms
10,248 KB |
testcase_03 | AC | 42 ms
10,316 KB |
testcase_04 | AC | 63 ms
10,408 KB |
testcase_05 | AC | 119 ms
10,580 KB |
testcase_06 | AC | 253 ms
11,000 KB |
testcase_07 | AC | 600 ms
11,788 KB |
testcase_08 | AC | 1,420 ms
13,540 KB |
testcase_09 | AC | 1,431 ms
13,540 KB |
testcase_10 | AC | 29 ms
10,248 KB |
testcase_11 | AC | 30 ms
10,248 KB |
testcase_12 | AC | 29 ms
10,248 KB |
testcase_13 | AC | 30 ms
10,248 KB |
testcase_14 | AC | 30 ms
10,248 KB |
ソースコード
# -*- coding: utf-8 -*- import sys sys.setrecursionlimit(10**9) input = sys.stdin.readline # python template for atcoder1 def manhattan(item1, item2): dist = abs(item1[0]-item2[0])+abs(item1[1]-item2[1]) #print("dist->", dist) return dist def calcCost(dropItem, last_visit, weight_sum): dist = manhattan(dropItem, last_visit) cost = (weight_sum+100)/120*dist ret = cost+dropItem[2] #print("ret->", ret) return ret SX, SY = map(int, input().split()) N = int(input()) items = [list(map(float, input().split())) for _ in range(N)] dp = [[float('inf')]*N for _ in range(1 << N)] dp[0][0] = 0 for i in range(1): dp[0][i] = 0 for mask in range(1 << N): for new_item in range(N): if mask >> new_item & 1: continue new_state = mask | 1 << new_item if mask == 0: weight_sum = 0 for loaded in range(N): if mask >> loaded & 1 == 0: weight_sum += items[loaded][2] cost = calcCost(items[new_item], [SX, SY], weight_sum) dp[new_state][new_item] = cost else: for last_visit in range(N): if mask >> last_visit & 1: weight_sum = 0 for loaded in range(N): if mask >> loaded & 1 == 0: weight_sum += items[loaded][2] cost = calcCost(items[new_item], items[last_visit], weight_sum) dp[new_state][new_item] = min( dp[new_state][new_item], dp[mask][last_visit]+cost) ans = float('inf') for i in range(N): ans = min(ans, dp[-1][i]+manhattan([SX, SY], items[i])*100/120) print(ans)