Submission #440487

#TimeUsernameProblemLanguageResultExecution timeMemory
440487SorahISAJelly Flavours (IOI20_jelly)C++17
100 / 100
46 ms588 KiB
#include "jelly.h" #include <bits/stdc++.h> using namespace std; using pii = pair<int, int>; template<typename T> using Prior = std::priority_queue<T>; template<typename T> using prior = std::priority_queue<T, vector<T>, greater<T>>; #define A first #define B second #define eb emplace_back #define pb pop_back #define pf pop_front #define ALL(x) begin(x), end(x) #define RALL(x) rbegin(x), rend(x) mt19937_64 rng(chrono::steady_clock::now().time_since_epoch().count()); int find_maximum_unique(int X, int Y, vector<int> _A, vector<int> _B) { int N = _A.size(); vector<pii> AB; for (int i = 0; i < N; ++i) AB.eb(_A[i], _B[i]); sort(ALL(AB)); /** * Sort items by A[i], then there must exist an place p \in [0, N] such that * - for items i which 0 \le i < p, we either buy it with A[i] or B[i] * - for items i which p \le i < N, we either buy it with B[i] or not buying it * * We use knapsack-dp to find the minimum cost of spending money on B[i] with * 0 \le i < p when p is a fixed number, and use a multiset to maintain a sorted * sequence on B[i] with p \le i < N. Knapsack-dp can be maintained in O(X) while * finding the maximum choice in multiset can be done in O(N \lg N). * * The overall time complexity is O(NX + N^2 \lg N). **/ int ans = 0; multiset<int> st(ALL(_B)); vector<int> dp(X+1, 0); /// normal knapsack dp for (int i = 0, totB = 0; i < N; ++i) { totB += AB[i].B; for (int j = X; j >= AB[i].A; --j) { dp[j] = max({dp[j], dp[j-1], dp[j - AB[i].A] + AB[i].B}); } /// get max answer /// st.erase(st.find(AB[i].B)); int cnt = i+1, sum = totB - dp[X]; for (auto x : st) { if (sum + x <= Y) sum += x, ++cnt; else break; } if (sum <= Y) ans = max(ans, cnt); } return ans; }
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