#1050403 (PyPy3) No.1678 Coin Trade (Multiple)

• 問題: No.1678 Coin Trade (Multiple)
• ユーザー: mkawa2
• 提出日時: 2025-03-07 19:11:06
• 言語: PyPy3 (7.3.15)
• 結果: TLE
• 実行時間: -
• コード長: 8,325 bytes
• コンパイル時間: 763 ms
• コンパイル使用メモリ: 82,380 KB
• 実行使用メモリ: 76,772 KB
• 最終ジャッジ日時: 2025-03-07 19:11:16
• 合計ジャッジ時間: 8,230 ms
• ジャッジサーバーID （参考情報）: judge5 / judge3

ファイルパターン	結果
sample	AC * 3
other	TLE * 1 -- * 55

ソースコード

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
import sys
# sys.setrecursionlimit(200005)
# sys.set_int_max_str_digits(200005)
int1 = lambda x: int(x)-1
pDB = lambda *x: print(*x, end="\n", file=sys.stderr)
p2D = lambda x: print(*x, sep="\n", end="\n\n", file=sys.stderr)
def II(): return int(sys.stdin.readline())
def LI(): return list(map(int, sys.stdin.readline().split()))
def LLI(rows_number): return [LI() for _ in range(rows_number)]
def LI1(): return list(map(int1, sys.stdin.readline().split()))
def LLI1(rows_number): return [LI1() for _ in range(rows_number)]
def SI(): return sys.stdin.readline().rstrip()
dij = [(0, 1), (-1, 0), (0, -1), (1, 0)]
# dij = [(0, 1), (-1, 0), (0, -1), (1, 0), (1, 1), (1, -1), (-1, 1), (-1, -1)]
# inf = -1-(-1 << 31)
inf = -1-(-1 << 62)
# md = 10**9+7
md = 998244353
from collections import deque
class MaxFlow():
    def __init__(self, n):
        self.n = n
        self.graph = [[] for _ in range(n)]
        self.pos = []
    def add_edge(self, fr, to, cap):
        m = len(self.pos)
        self.pos.append((fr, len(self.graph[fr])))
        fr_id = len(self.graph[fr])
        to_id = len(self.graph[to])
        if fr == to: to_id += 1
        self.graph[fr].append([to, to_id, cap])
        self.graph[to].append([fr, fr_id, 0])
        return m
    def get_edge(self, idx):
        to, rev, cap = self.graph[self.pos[idx][0]][self.pos[idx][1]]
        rev_to, rev_rev, rev_cap = self.graph[to][rev]
        return rev_to, to, cap + rev_cap, rev_cap
    def edges(self):
        m = len(self.pos)
        for i in range(m):
            yield self.get_edge(i)
    def dfs(self, s, t, up):
        stack = [t]
        while stack:
            v = stack.pop()
            if v == s:
                flow = up
                for v in stack:
                    to, rev, cap = self.graph[v][self.iter[v]]
                    flow = min(flow, self.graph[to][rev][2])
                for v in stack:
                    self.graph[v][self.iter[v]][2] += flow
                    to, rev, cap = self.graph[v][self.iter[v]]
                    self.graph[to][rev][2] -= flow
                return flow
            lv = self.level[v]
            for i in range(self.iter[v], len(self.graph[v])):
                to, rev, cap = self.graph[v][i]
                if lv > self.level[to] and self.graph[to][rev][2]:
                    self.iter[v] = i
                    stack.append(v)
                    stack.append(to)
                    break
            else:
                self.iter[v] = len(self.graph[v])
                self.level[v] = self.n
        return 0
    def max_flow(self, s, t):
        return self.max_flow_with_limit(s, t, 2**63 - 1)
    def max_flow_with_limit(self, s, t, limit):
        flow = 0
        while flow < limit:
            self.level = [-1] * self.n
            self.level[s] = 0
            queue = deque()
            queue.append(s)
            while queue:
                v = queue.popleft()
                for to, rev, cap in self.graph[v]:
                    if cap == 0 or self.level[to] >= 0: continue
                    self.level[to] = self.level[v] + 1
                    if to == t: break
                    queue.append(to)
            if self.level[t] == -1: break
            self.iter = [0] * self.n
            while flow < limit:
                f = self.dfs(s, t, limit - flow)
                if not f: break
                flow += f
        return flow
class CostScalingGraph():
    def __init__(self, n):
        self.n = n
        self.edges = []
        self.excess = [0] * n
        self.maxcost = 0
        self.graph = [[] for _ in range(self.n)]
        self.pos = []
        self.dual = [0] * n
    def add_edge(self, fr, to, lower, upper, cost):
        self.maxcost = max(self.maxcost, cost, -cost)
        self.edges.append([fr, to, lower, upper, 0, cost])
    def add_excess(self, v, x):
        self.excess[v] += x
    def solve(self):
        mf = MaxFlow(self.n + 2)
        sv = self.n
        tv = self.n + 1
        for fr, to, lower, upper, flow, cost in self.edges:
            self.excess[to] += lower
            self.excess[fr] -= lower
            mf.add_edge(fr, to, upper - lower)
        excess_s_sum = excess_t_sum = 0
        for i in range(self.n):
            if self.excess[i] > 0:
                excess_s_sum += self.excess[i]
                mf.add_edge(sv, i, self.excess[i])
            if self.excess[i] < 0:
                excess_t_sum -= self.excess[i]
                mf.add_edge(i, tv, -self.excess[i])
        if excess_s_sum != excess_t_sum or mf.max_flow(sv, tv) != excess_s_sum:
            return False, 0
        m = len(self.edges)
        for i in range(m):
            fr, to, cap, flow = mf.get_edge(i)
            cost = self.edges[i][5] * (self.n + 1)
            fr_id = len(self.graph[fr])
            to_id = len(self.graph[to])
            if fr == to: to_id += 1
            self.pos.append([fr, fr_id])
            self.graph[fr].append([to, to_id, cap - flow, cost])
            self.graph[to].append([fr, fr_id, flow, -cost])
        self.eps = (self.n + 1) * self.maxcost
        while self.eps > 1:
            self.eps = max(self.eps >> 2, 1)
            self.refine()
        res = 0
        for i in range(m):
            fr, _, lower, upper, flow, cost = self.edges[i]
            to, rev, cap, _ = self.graph[self.pos[i][0]][self.pos[i][1]]
            self.edges[i][4] = upper - cap
            res += (upper - cap) * cost
        self.dual = [0] * self.n
        while True:
            update = False
            for i in range(self.n):
                for to, rev, cap, cost in self.graph[i]:
                    if cap == 0: continue
                    cost = self.dual[i] + cost // (self.n + 1)
                    if cost < self.dual[to]:
                        self.dual[to] = cost
                        update = True
            if not update: break
        return True, res
    def refine(self):
        excess = [0] * self.n
        for u in range(self.n):
            for v, e in enumerate(self.graph[u]):
                to, rev, cap, cost = e
                if cap != 0 and cost + self.dual[u] - self.dual[to] < 0:
                    excess[u] -= cap
                    excess[to] += cap
                    self.graph[to][rev][2] += cap
                    self.graph[u][v][2] -= cap
        actives_on = [False] * self.n
        actives = deque()
        iter = [0] * self.n
        for i in range(self.n):
            if excess[i] > 0:
                actives.append(i)
                actives_on[i] = True
        while actives:
            u = actives.popleft()
            actives_on[u] = False
            for i in range(iter[u], len(self.graph[u])):
                to, rev, cap, cost = self.graph[u][i]
                if cap != 0 and cost + self.dual[u] - self.dual[to] < 0:
                    cap = min(excess[u], cap)
                    excess[u] -= cap
                    excess[to] += cap
                    self.graph[to][rev][2] += cap
                    self.graph[u][i][2] -= cap
                    if not actives_on[to] and excess[to] > 0:
                        actives_on[to] = True
                        actives.append(to)
                    if excess[u] == 0:
                        iter[u] = i
                        break
            else:
                iter[u] = len(self.graph[u])
            if excess[u] > 0:
                iter[u] = 0
                down = (self.n + 1) * self.maxcost
                for to, rev, cap, cost in self.graph[u]:
                    if cap != 0:
                        down = min(down, self.eps + cost + self.dual[u] - self.dual[to])
                self.dual[u] -= down
                actives.append(u)
                actives_on[u] = True
        self.eps = 0
        for u in range(self.n):
            for to, rev, cap, cost in self.graph[u]:
                if cap != 0:
                    self.eps = max(self.eps, -cost - self.dual[u] + self.dual[to])
mx=10**9
n,k=LI()
mf=CostScalingGraph(n)
aa=[]
for i in range(n):
    if i:mf.add_edge(i-1,i,0,n,mx)
    a,m=LI()
    aa.append(a)
    for j in LI1():
        if j<i and aa[j]<a:
            mf.add_edge(j,i,0,1,mx*(i-j)-a+aa[j])
mf.add_excess(0,k)
mf.add_excess(n-1,-k)
f=mf.solve()
ans = mx*(n-1)*k-f[1]
print(ans)
 
 
הההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההה
XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX