結果
| 問題 |
No.1341 真ん中を入れ替えて門松列
|
| コンテスト | |
| ユーザー |
👑 tatyam
|
| 提出日時 | 2021-01-16 03:38:57 |
| 言語 | C++17 (gcc 13.3.0 + boost 1.87.0) |
| 結果 |
TLE
|
| 実行時間 | - |
| コード長 | 9,270 bytes |
| コンパイル時間 | 2,792 ms |
| コンパイル使用メモリ | 223,844 KB |
| 最終ジャッジ日時 | 2025-01-17 21:12:26 |
|
ジャッジサーバーID (参考情報) |
judge4 / judge4 |
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| ファイルパターン | 結果 |
|---|---|
| sample | AC * 5 |
| other | AC * 4 TLE * 10 |
ソースコード
#include <bits/stdc++.h>
using namespace std;
enum Objective {
MINIMIZE = 1,
MAXIMIZE = -1,
};
enum class Status {
OPTIMAL,
INFEASIBLE,
};
template <class Flow, class Cost, Objective objective = Objective::MINIMIZE, Flow SCALING_FACTOR = 2>
class MinCostFlow {
using V_id = uint32_t;
using E_id = uint32_t;
class Edge {
friend class MinCostFlow;
V_id src, dst;
Flow flow, cap;
Cost cost;
E_id rev;
public:
Edge() = default;
Edge(const V_id src, const V_id dst, const Flow cap, const Cost cost,
const E_id rev)
: src(src), dst(dst), flow(0), cap(cap), cost(cost), rev(rev) {}
[[nodiscard]] Flow residual_cap() const { return cap - flow; }
};
public:
class EdgePtr {
friend class MinCostFlow;
const MinCostFlow *instance;
const V_id v;
const E_id e;
EdgePtr(const MinCostFlow *instance, const V_id v, const E_id e)
: instance(instance), v(v), e(e) {}
[[nodiscard]] const Edge &edge() const { return instance->g[v][e]; }
[[nodiscard]] const Edge &rev() const {
const Edge &e = edge();
return instance->g[e.dst][e.rev];
}
public:
[[nodiscard]] V_id src() const { return rev().dst; }
[[nodiscard]] V_id dst() const { return edge().dst; }
[[nodiscard]] Flow flow() const { return edge().flow; }
[[nodiscard]] Flow lower() const { return -rev().cap; }
[[nodiscard]] Flow upper() const { return edge().cap; }
[[nodiscard]] Cost cost() const { return edge().cost; }
[[nodiscard]] Cost gain() const { return -edge().cost; }
};
private:
V_id n;
std::vector<std::vector<Edge>> g;
std::vector<Flow> b;
public:
MinCostFlow() : n(0) {}
V_id add_vertex() {
++n;
g.resize(n);
b.resize(n);
return n-1;
}
std::vector<V_id> add_vertices(const size_t size) {
std::vector<V_id> ret;
for (V_id i = 0; i < size; ++i) ret.emplace_back(n + i);
n += size;
g.resize(n);
b.resize(n);
return ret;
}
EdgePtr add_edge(const V_id src, const V_id dst, const Flow lower,
const Flow upper, const Cost cost) {
const E_id e = g[src].size(), re = src == dst ? e + 1 : g[dst].size();
assert(lower <= upper);
g[src].emplace_back(Edge{src, dst, upper, cost * objective, re});
g[dst].emplace_back(Edge{dst, src, -lower, -cost * objective, e});
return EdgePtr{this, src, e};
}
void add_supply(const V_id v, const Flow amount) { b[v] += amount; }
void add_demand(const V_id v, const Flow amount) { b[v] -= amount; }
private:
// Variables used in calculation
static Cost constexpr unreachable = std::numeric_limits<Cost>::max();
Cost farthest;
std::vector<Cost> potential;
std::vector<Cost> dist;
std::vector<Edge *> parent; // out-forrest.
std::priority_queue<std::pair<Cost, int>, std::vector<std::pair<Cost, int>>,
std::greater<>>
pq; // should be empty outside of dual()
std::vector<V_id> excess_vs, deficit_vs;
Edge &rev(const Edge &e) { return g[e.dst][e.rev]; }
void push(Edge &e, const Flow amount) {
e.flow += amount;
g[e.dst][e.rev].flow -= amount;
}
Cost residual_cost(const V_id src, const V_id dst, const Edge &e) {
return e.cost + potential[src] - potential[dst];
}
bool dual(const Flow delta) {
dist.assign(n, unreachable);
parent.assign(n, nullptr);
excess_vs.erase(std::remove_if(std::begin(excess_vs), std::end(excess_vs),
[&](const V_id v) { return b[v] < delta; }),
std::end(excess_vs));
deficit_vs.erase(std::remove_if(std::begin(deficit_vs),
std::end(deficit_vs),
[&](const V_id v) { return b[v] > -delta; }),
std::end(deficit_vs));
for (const auto v : excess_vs) pq.emplace(dist[v] = 0, v);
farthest = 0;
std::size_t deficit_count = 0;
while (!pq.empty()) {
const auto [d, u] = pq.top();
pq.pop();
if (dist[u] < d) continue;
farthest = d;
if (b[u] <= -delta) ++deficit_count;
if (deficit_count >= deficit_vs.size()) break;
for (auto &e : g[u]) {
if (e.residual_cap() < delta) continue;
const auto v = e.dst;
const auto new_dist = d + residual_cost(u, v, e);
if (new_dist >= dist[v]) continue;
pq.emplace(dist[v] = new_dist, v);
parent[v] = &e;
}
}
pq = decltype(pq)(); // pq.clear() doesn't exist.
for (V_id v = 0; v < n; ++v) {
potential[v] += std::min(dist[v], farthest);
}
return deficit_count > 0;
}
void primal(const Flow delta) {
for (const auto t : deficit_vs) {
if (dist[t] > farthest) continue;
Flow f = -b[t];
V_id v;
for (v = t; parent[v] != nullptr && f >= delta; v = parent[v]->src) {
f = std::min(f, parent[v]->residual_cap());
}
f = std::min(f, b[v]);
if (f < delta) continue;
for (v = t; parent[v] != nullptr;) {
auto &e = *parent[v];
push(e, f);
const size_t u = parent[v]->src;
parent[v] = nullptr;
v = u;
}
b[t] += f;
b[v] -= f;
}
}
void saturate_negative(const Flow delta) {
excess_vs.clear();
deficit_vs.clear();
for (auto &es : g) for (auto &e : es) {
const Flow rcap = e.residual_cap();
const Cost rcost = residual_cost(e.src, e.dst, e);
if (rcost < 0 && rcap >= delta) {
push(e, rcap);
b[e.src] -= rcap;
b[e.dst] += rcap;
}
}
for (V_id v = 0; v < n; ++v) if (b[v] != 0) {
(b[v] > 0 ? excess_vs : deficit_vs).emplace_back(v);
}
}
public:
std::pair<Status, Cost> solve() {
potential.resize(n);
for (auto &es : g) for (auto &e : es) {
const Flow rcap = e.residual_cap();
if (rcap < 0) {
push(e, rcap);
b[e.src] -= rcap;
b[e.dst] += rcap;
}
}
Flow inf_flow = 1;
for (const auto &es : g) for (const auto &e : es) inf_flow = std::max(inf_flow, e.residual_cap());
Flow delta = 1;
while (delta <= inf_flow) delta *= SCALING_FACTOR;
for (delta /= SCALING_FACTOR; delta; delta /= SCALING_FACTOR) {
saturate_negative(delta);
while (dual(delta)) primal(delta);
}
Cost value = 0;
for (const auto &es : g) for (const auto &e : es) {
value += e.flow * e.cost;
}
value /= 2;
if (excess_vs.empty() && deficit_vs.empty()) {
return { Status::OPTIMAL, value / objective };
} else {
return { Status::INFEASIBLE, value / objective };
}
}
template<class T>
T get_result_value() {
T value = 0;
for (const auto &es : g) for (const auto &e : es) {
value += (T)(e.flow) * (T)(e.cost);
}
value /= (T)2;
return value / objective;
}
std::vector<Cost> get_potential() {
// Not strictly necessary, but re-calculate potential to bound the potential values,
// plus make them somewhat canonical so that it is robust for the algorithm chaneges.
std::fill(std::begin(potential), std::end(potential), 0);
for (size_t i = 0; i < n; ++i) for (const auto &es : g) for (const auto &e : es)
if (e.residual_cap() > 0) potential[e.dst] = std::min(potential[e.dst], potential[e.src] + e.cost);
return potential;
}
std::vector<size_t> get_cut() {
std::vector<size_t> res;
if (excess_vs.empty()) return res;
for (size_t v = 0; v < n; ++v) {
if (deficit_vs.empty() || (dist[v] < unreachable))
res.emplace_back(v);
}
return res;
}
};
using ll = int64_t;
int main(){
cin.tie(nullptr);
ios::sync_with_stdio(false);
ll N, M;
cin >> N >> M;
vector<ll> A(N), B(N), C(N);
for(ll i = 0; i < N; i++){
cin >> A[i] >> B[i] >> C[i];
if(A[i] > C[i]) swap(A[i], C[i]);
}
MinCostFlow<ll, ll> g;
g.add_vertices(N * 4 + 1);
const ll S = N * 4;
for(ll i = 0; i < N; i++) g.add_edge(S, i, 0, 1, 0);
vector<ll> index(N);
iota(index.begin(), index.end(), 0);
sort(index.begin(), index.end(), [&](ll x, ll y){ return A[x] < A[y]; });
for(ll i = 0; i < N; i++){
auto p = partition_point(index.begin(), index.end(), [&](ll j){ return A[j] <= B[i]; });
if(p == index.end()) continue;
g.add_edge(i, *p + N, 0, 1, 0);
}
for(ll i = 0; i + 1 < N; i++) g.add_edge(index[i] + N, index[i + 1] + N, 0, N, 0);
for(ll i = 0; i < N; i++) g.add_edge(i + N, i + N * 3, 0, 1, -C[i]);
sort(index.begin(), index.end(), [&](ll x, ll y){ return C[x] > C[y]; });
for(ll i = 0; i < N; i++){
auto p = partition_point(index.begin(), index.end(), [&](ll j){ return C[j] >= B[i]; });
if(p == index.end()) continue;
g.add_edge(i, *p + N * 2, 0, 1, -B[i]);
}
for(ll i = 0; i + 1 < N; i++) g.add_edge(index[i] + N * 2, index[i + 1] + N * 2, 0, N, 0);
for(ll i = 0; i < N; i++) g.add_edge(i + N * 2, i + N * 3, 0, 1, 0);
for(ll i = 0; i < N; i++) g.add_demand(i + N * 3, 1);
g.add_supply(S, N);
const auto status = g.solve().first;
if(status == Status::INFEASIBLE) return puts("NO") & 0;
puts("YES");
puts(-g.get_result_value<ll>() >= M ? "KADOMATSU!" : "NO");
}
tatyam