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maximum-and-sum-of-array.cpp
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maximum-and-sum-of-array.cpp
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// Time: O(n^3)
// Space: O(n^2)
// weighted bipartite matching solution
class Solution {
public:
int maximumANDSum(vector<int>& nums, int numSlots) {
vector<vector<int>> adj(2 * numSlots, vector<int>(2 * numSlots));
for (int i = 0; i < 2 * numSlots; ++i) {
for (int j = 0; j < 2 * numSlots; ++j) {
adj[i][j] = -((i < size(nums) ? nums[i] : 0) & (1 + j / 2));
}
}
return -hungarian(adj).first;
}
private:
// Template modified from:
// https://github.com/kth-competitive-programming/kactl/blob/main/content/graph/WeightedMatching.h
pair<int, vector<int>> hungarian(const vector<vector<int>> &a) { // Time: O(n^2 * m), Space: O(n + m)
if (a.empty()) return {0, {}};
int n = size(a) + 1, m = size(a[0]) + 1;
vector<int> u(n), v(m), p(m), ans(n - 1);
for (int i = 1; i < n; ++i) {
p[0] = i;
int j0 = 0; // add "dummy" worker 0
vector<int> dist(m, numeric_limits<int>::max()), pre(m, -1);
vector<bool> done(m + 1);
do { // dijkstra
done[j0] = true;
int i0 = p[j0], j1, delta = numeric_limits<int>::max();
for (int j = 1; j < m; ++j) {
if (!done[j]) {
auto cur = a[i0 - 1][j - 1] - u[i0] - v[j];
if (cur < dist[j]) dist[j] = cur, pre[j] = j0;
if (dist[j] < delta) delta = dist[j], j1 = j;
}
}
for (int j = 0; j < m; ++j) {
if (done[j]) u[p[j]] += delta, v[j] -= delta;
else dist[j] -= delta;
}
j0 = j1;
} while (p[j0]);
while (j0) { // update alternating path
int j1 = pre[j0];
p[j0] = p[j1], j0 = j1;
}
}
for (int j = 1; j < m; ++j) if (p[j]) ans[p[j] - 1] = j - 1;
return {-v[0], ans}; // min cost
}
};
// Time: O(s * 3^s)
// Space: O(3^s)
// bottom-up dp (hard to implement but faster)
class Solution2 {
public:
int maximumANDSum(vector<int>& nums, int numSlots) {
const auto& count = [](int x) {
int result = 0;
for (; x; x /= 3) {
result += x % 3;
}
return result;
};
vector<int> dp(pow(3, numSlots));
for (int mask = 1; mask < size(dp); ++mask) {
const int i = count(mask) - 1;
const int x = (i < size(nums)) ? nums[i] : 0;
for (int slot = 1, base = 1; slot <= numSlots; ++slot, base *= 3) {
if (mask / base % 3) {
dp[mask] = max(dp[mask], (x & slot) + dp[mask - base]);
}
}
}
return dp.back();
}
};