結果

問題 No.1301 Strange Graph Shortest Path
ユーザー Kite_kumaKite_kuma
提出日時 2020-10-30 21:27:22
言語 Python3
(3.12.2 + numpy 1.26.4 + scipy 1.12.0)
結果
TLE  
実行時間 -
コード長 5,176 bytes
コンパイル時間 356 ms
コンパイル使用メモリ 13,056 KB
実行使用メモリ 236,948 KB
最終ジャッジ日時 2024-09-13 00:19:53
合計ジャッジ時間 5,809 ms
ジャッジサーバーID
（参考情報） 		judge3 / judge2
このコードへのチャレンジ
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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 33 ms
18,204 KB
testcase_01 AC 33 ms
11,136 KB
testcase_02 TLE -
testcase_03 -- -
testcase_04 -- -
testcase_05 -- -
testcase_06 -- -
testcase_07 -- -
testcase_08 -- -
testcase_09 -- -
testcase_10 -- -
testcase_11 -- -
testcase_12 -- -
testcase_13 -- -
testcase_14 -- -
testcase_15 -- -
testcase_16 -- -
testcase_17 -- -
testcase_18 -- -
testcase_19 -- -
testcase_20 -- -
testcase_21 -- -
testcase_22 -- -
testcase_23 -- -
testcase_24 -- -
testcase_25 -- -
testcase_26 -- -
testcase_27 -- -
testcase_28 -- -
testcase_29 -- -
testcase_30 -- -
testcase_31 -- -
testcase_32 -- -
testcase_33 -- -
testcase_34 -- -
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 sys
import heapq

input = sys.stdin.readline
BIG = 10 ** 9


class mcf_graph_int_cost:
    """
    頂点数、及び、costの総和が、4294967295 (== (1 << 32) - 1) を超えない前提下での高速な実装。
    後者は超えても一応動く。
    """

    def __init__(self, n):
        self.n = n
        self.pos = []
        self.g = [[] for _ in range(n)]

    def add_edge(self, from_, to, cap, cost):
        # assert 0 <= from_ < self.n
        # assert 0 <= to < self.n
        m = len(self.pos)
        self.pos.append((from_, len(self.g[from_])))
        self.g[from_].append(self.__class__._edge(
            to, len(self.g[to]), cap, cost))
        self.g[to].append(self.__class__._edge(
            from_, len(self.g[from_]) - 1, 0, -cost))
        return m

    class edge:
        def __init__(self, from_, to, cap, flow, cost):
            self.from_ = from_
            self.to = to
            self.cap = cap
            self.flow = flow
            self.cost = cost

    def get_edge(self, i):
        _e = self.g[self.pos[i][0]][self.pos[i][1]]
        _re = self.g[_e.to][_e.rev]
        return self.__class__.edge(self.pos[i][0], _e.to, _e.cap + _re.cap, _re.cap, _e.cost)

    def edges(self):
        ret = []
        for i in range(len(self.pos)):
            _e = self.g[self.pos[i][0]][self.pos[i][1]]
            _re = self.g[_e.to][_e.rev]
            ret.append(self.__class__.edge(
                self.pos[i][0], _e.to, _e.cap + _re.cap, _re.cap, _e.cost))
        return ret

    def _dual_ref(self):
        self.dist = [4294967295] * self.n
        self.pv = [-1] * self.n
        self.pe = [-1] * self.n
        self.vis = [False] * self.n

        que = [s]
        self.dist[s] = 0
        while que:
            v = heapq.heappop(que) & 4294967295
            if self.vis[v]:
                continue
            self.vis[v] = True
            if v == t:
                break
            for i in range(len(self.g[v])):
                e = self.g[v][i]
                if self.vis[e.to] or e.cap == 0:
                    continue
                cost = e.cost - self.dual[e.to] + self.dual[v]
                if self.dist[e.to] > self.dist[v] + cost:
                    self.dist[e.to] = self.dist[v] + cost
                    self.pv[e.to] = v
                    self.pe[e.to] = i
                    heapq.heappush(que, ((self.dist[e.to] << 32) + e.to))
        if not self.vis[t]:
            return False

        for v in range(self.n):
            if not self.vis[v]:
                continue
            self.dual[v] -= self.dist[t] - self.dist[v]

        return True

    def slope(self, s, t, flow_limit=4294967295):
        # assert 0 <= s < self.n
        # assert 0 <= t < self.n
        # assert s != t

        self.dual = [0] * self.n
        self.dist = [4294967295] * self.n
        self.pv = [-1] * self.n
        self.pe = [-1] * self.n
        self.vis = [False] * self.n

        flow = 0
        cost = 0
        prev_cost = -1
        result = [(flow, cost)]
        while flow < flow_limit:
            if not self._dual_ref():
                break
            c = flow_limit - flow
            v = t
            while v != s:
                c = min(c, self.g[self.pv[v]][self.pe[v]].cap)
                v = self.pv[v]
            v = t
            while v != s:
                e = self.g[self.pv[v]][self.pe[v]]
                e.cap -= c
                self.g[v][e.rev].cap += c
                v = self.pv[v]
            d = -self.dual[s]
            flow += c
            cost += c * d
            if prev_cost == d:
                result.pop()
            result.append((flow, cost))
            prev_cost = cost
        return result

    def flow(self, s, t, flow_limit=4294967295):
        return self.slope(s, t, flow_limit)[-1]

    class _edge:
        def __init__(self, to, rev, cap, cost):
            self.to = to
            self.rev = rev
            self.cap = cap
            self.cost = cost


# N, K = map(int, input().split())

# g = mcf_graph_int_cost(2 * N + 2)
# s = 2 * N
# t = 2 * N + 1

# g.add_edge(s, t, N * K, BIG)
# for i in range(N):
#     g.add_edge(s, i, K, 0)
#     g.add_edge(N + i, t, K, 0)

# for i in range(N):
#     As = map(int, input().split())
#     for j, A in enumerate(As):
#         g.add_edge(i, N + j, 1, BIG - A)

# result = g.flow(s, t, N * K)

# print(N * K * BIG - result[1])

# grid = [['.' for _ in range(N)] for _ in range(N)]
# edges = g.edges()
# for e in edges:
#     if e.from_ == s or e.to == t or e.flow == 0:
#         continue
#     grid[e.from_][e.to - N] = 'X'

# for row in grid:
#     print(''.join(row))

n, m = map(int, input().split())
s, t = 0, n - 1
graph = mcf_graph_int_cost(n + m)
for i in range(m):
    u, v, c, d = map(int, input().split())
    assert 1 <= u <= n and 1 <= v <= n and c <= d
    u -= 1
    v -= 1
    mid = n + i
    graph.add_edge(u, mid, 2, c)
    graph.add_edge(mid, v, 1, 0)
    graph.add_edge(mid, v, 1, d - c)
    graph.add_edge(v, mid, 2, c)
    graph.add_edge(mid, u, 1, 0)
    graph.add_edge(mid, u, 1, d - c)

flow, cost = graph.flow(s, t, 2)
assert flow == 2
print(cost)
0