結果

問題 No.654 Air E869120
ユーザー mo124121mo124121
提出日時 2023-09-07 22:35:41
言語 PyPy3
(7.3.15)
結果
WA  
実行時間 -
コード長 5,847 bytes
コンパイル時間 254 ms
コンパイル使用メモリ 82,132 KB
実行使用メモリ 80,564 KB
最終ジャッジ日時 2024-06-25 16:11:00
合計ジャッジ時間 7,577 ms
ジャッジサーバーID
（参考情報） 		judge5 / judge4
このコードへのチャレンジ
（要ログイン）

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 69 ms
69,964 KB
testcase_01 AC 71 ms
69,128 KB
testcase_02 AC 68 ms
68,428 KB
testcase_03 AC 71 ms
69,424 KB
testcase_04 AC 68 ms
68,968 KB
testcase_05 AC 68 ms
68,812 KB
testcase_06 AC 70 ms
69,700 KB
testcase_07 AC 69 ms
69,020 KB
testcase_08 AC 68 ms
68,896 KB
testcase_09 AC 69 ms
70,408 KB
testcase_10 WA -
testcase_11 WA -
testcase_12 WA -
testcase_13 WA -
testcase_14 WA -
testcase_15 WA -
testcase_16 AC 202 ms
80,128 KB
testcase_17 AC 213 ms
80,208 KB
testcase_18 AC 179 ms
80,212 KB
testcase_19 AC 205 ms
80,072 KB
testcase_20 AC 159 ms
80,352 KB
testcase_21 AC 157 ms
79,992 KB
testcase_22 AC 131 ms
79,096 KB
testcase_23 AC 146 ms
80,320 KB
testcase_24 AC 163 ms
80,192 KB
testcase_25 AC 125 ms
78,996 KB
testcase_26 AC 141 ms
78,588 KB
testcase_27 AC 125 ms
78,584 KB
testcase_28 AC 130 ms
78,936 KB
testcase_29 AC 125 ms
78,508 KB
testcase_30 AC 120 ms
78,788 KB
testcase_31 AC 121 ms
78,580 KB
testcase_32 AC 116 ms
78,820 KB
testcase_33 AC 119 ms
78,828 KB
testcase_34 AC 117 ms
78,776 KB
testcase_35 AC 67 ms
67,760 KB
testcase_36 AC 67 ms
68,108 KB
testcase_37 AC 70 ms
68,236 KB
testcase_38 AC 68 ms
68,928 KB
testcase_39 AC 73 ms
70,452 KB
権限があれば一括ダウンロードができます

ソースコード

diff # 

import types

_atcoder_code = """
# Python port of AtCoder Library.

__version__ = '0.0.1'
"""

atcoder = types.ModuleType('atcoder')
exec(_atcoder_code, atcoder.__dict__)

_atcoder_maxflow_code = """
from typing import NamedTuple, Optional, List, cast


class MFGraph:
    class Edge(NamedTuple):
        src: int
        dst: int
        cap: int
        flow: int

    class _Edge:
        def __init__(self, dst: int, cap: int) -> None:
            self.dst = dst
            self.cap = cap
            self.rev: Optional[MFGraph._Edge] = None

    def __init__(self, n: int) -> None:
        self._n = n
        self._g: List[List[MFGraph._Edge]] = [[] for _ in range(n)]
        self._edges: List[MFGraph._Edge] = []

    def add_edge(self, src: int, dst: int, cap: int) -> int:
        assert 0 <= src < self._n
        assert 0 <= dst < self._n
        assert 0 <= cap
        m = len(self._edges)
        e = MFGraph._Edge(dst, cap)
        re = MFGraph._Edge(src, 0)
        e.rev = re
        re.rev = e
        self._g[src].append(e)
        self._g[dst].append(re)
        self._edges.append(e)
        return m

    def get_edge(self, i: int) -> Edge:
        assert 0 <= i < len(self._edges)
        e = self._edges[i]
        re = cast(MFGraph._Edge, e.rev)
        return MFGraph.Edge(
            re.dst,
            e.dst,
            e.cap + re.cap,
            re.cap
        )

    def edges(self) -> List[Edge]:
        return [self.get_edge(i) for i in range(len(self._edges))]

    def change_edge(self, i: int, new_cap: int, new_flow: int) -> None:
        assert 0 <= i < len(self._edges)
        assert 0 <= new_flow <= new_cap
        e = self._edges[i]
        e.cap = new_cap - new_flow
        assert e.rev is not None
        e.rev.cap = new_flow

    def flow(self, s: int, t: int, flow_limit: Optional[int] = None) -> int:
        assert 0 <= s < self._n
        assert 0 <= t < self._n
        assert s != t
        if flow_limit is None:
            flow_limit = cast(int, sum(e.cap for e in self._g[s]))

        current_edge = [0] * self._n
        level = [0] * self._n

        def fill(arr: List[int], value: int) -> None:
            for i in range(len(arr)):
                arr[i] = value

        def bfs() -> bool:
            fill(level, self._n)
            queue = []
            q_front = 0
            queue.append(s)
            level[s] = 0
            while q_front < len(queue):
                v = queue[q_front]
                q_front += 1
                next_level = level[v] + 1
                for e in self._g[v]:
                    if e.cap == 0 or level[e.dst] <= next_level:
                        continue
                    level[e.dst] = next_level
                    if e.dst == t:
                        return True
                    queue.append(e.dst)
            return False

        def dfs(lim: int) -> int:
            stack = []
            edge_stack: List[MFGraph._Edge] = []
            stack.append(t)
            while stack:
                v = stack[-1]
                if v == s:
                    flow = min(lim, min(e.cap for e in edge_stack))
                    for e in edge_stack:
                        e.cap -= flow
                        assert e.rev is not None
                        e.rev.cap += flow
                    return flow
                next_level = level[v] - 1
                while current_edge[v] < len(self._g[v]):
                    e = self._g[v][current_edge[v]]
                    re = cast(MFGraph._Edge, e.rev)
                    if level[e.dst] != next_level or re.cap == 0:
                        current_edge[v] += 1
                        continue
                    stack.append(e.dst)
                    edge_stack.append(re)
                    break
                else:
                    stack.pop()
                    if edge_stack:
                        edge_stack.pop()
                    level[v] = self._n
            return 0

        flow = 0
        while flow < flow_limit:
            if not bfs():
                break
            fill(current_edge, 0)
            while flow < flow_limit:
                f = dfs(flow_limit - flow)
                flow += f
                if f == 0:
                    break
        return flow

    def min_cut(self, s: int) -> List[bool]:
        visited = [False] * self._n
        stack = [s]
        visited[s] = True
        while stack:
            v = stack.pop()
            for e in self._g[v]:
                if e.cap > 0 and not visited[e.dst]:
                    visited[e.dst] = True
                    stack.append(e.dst)
        return visited
"""

atcoder.maxflow = types.ModuleType('atcoder.maxflow')
exec(_atcoder_maxflow_code, atcoder.maxflow.__dict__)
maxflow = atcoder.maxflow

from collections import defaultdict
# from atcoder import maxflow

N, M, d = map(int, input().split())

G = maxflow.MFGraph(N * 2 + M)
s = N
t = N - 1

E = []


size = -1


def gen_node():
    global size
    size += 1
    return size


G = maxflow.MFGraph(M * 4 + 2)

nodes_from = defaultdict(list)
nodes_to = defaultdict(list)
s = gen_node()
nodes_from[0].append((0, s))

for i in range(M):
    u, v, p, q, w = map(int, input().split())
    u -= 1
    v -= 1

    frm = gen_node()
    to = gen_node()
    ready = gen_node()
    G.add_edge(frm, to, w)
    G.add_edge(to, ready, w)
    nodes_from[u].append((p, frm))
    nodes_to[v].append((q, to))
    nodes_from[v].append((q + d, ready))


t = gen_node()
nodes_to[N - 1].append((10**9, t))

INF = 10**18
for u in nodes_from:
    lst = sorted(nodes_from[u])
    for (_, x), (_, y) in zip(lst, lst[1:]):
        G.add_edge(x, y, INF)

for v in nodes_to:
    lst = sorted(nodes_to[v])
    for (_, x), (_, y) in zip(lst, lst[1:]):
        G.add_edge(x, y, INF)

f = G.flow(s, t)

print(f)
0