hello-algo/en/codes/cpp/chapter_dynamic_programming/knapsack.cpp

109 lines
3.7 KiB
C++

#include <algorithm>
#include <iostream>
#include <vector>
using namespace std;
/* 0-1 Knapsack: Brute force search */
int knapsackDFS(vector<int> &wgt, vector<int> &val, int i, int c) {
// If all items have been chosen or the knapsack has no remaining capacity, return value 0
if (i == 0 || c == 0) {
return 0;
}
// If exceeding the knapsack capacity, can only choose not to put it in the knapsack
if (wgt[i - 1] > c) {
return knapsackDFS(wgt, val, i - 1, c);
}
// Calculate the maximum value of not putting in and putting in item i
int no = knapsackDFS(wgt, val, i - 1, c);
int yes = knapsackDFS(wgt, val, i - 1, c - wgt[i - 1]) + val[i - 1];
// Return the greater value of the two options
return max(no, yes);
}
/* 0-1 Knapsack: Memoized search */
int knapsackDFSMem(vector<int> &wgt, vector<int> &val, vector<vector<int>> &mem, int i, int c) {
// If all items have been chosen or the knapsack has no remaining capacity, return value 0
if (i == 0 || c == 0) {
return 0;
}
// If there is a record, return it
if (mem[i][c] != -1) {
return mem[i][c];
}
// If exceeding the knapsack capacity, can only choose not to put it in the knapsack
if (wgt[i - 1] > c) {
return knapsackDFSMem(wgt, val, mem, i - 1, c);
}
// Calculate the maximum value of not putting in and putting in item i
int no = knapsackDFSMem(wgt, val, mem, i - 1, c);
int yes = knapsackDFSMem(wgt, val, mem, i - 1, c - wgt[i - 1]) + val[i - 1];
// Record and return the greater value of the two options
mem[i][c] = max(no, yes);
return mem[i][c];
}
/* 0-1 Knapsack: Dynamic programming */
int knapsackDP(vector<int> &wgt, vector<int> &val, int cap) {
int n = wgt.size();
// Initialize dp table
vector<vector<int>> dp(n + 1, vector<int>(cap + 1, 0));
// State transition
for (int i = 1; i <= n; i++) {
for (int c = 1; c <= cap; c++) {
if (wgt[i - 1] > c) {
// If exceeding the knapsack capacity, do not choose item i
dp[i][c] = dp[i - 1][c];
} else {
// The greater value between not choosing and choosing item i
dp[i][c] = max(dp[i - 1][c], dp[i - 1][c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[n][cap];
}
/* 0-1 Knapsack: Space-optimized dynamic programming */
int knapsackDPComp(vector<int> &wgt, vector<int> &val, int cap) {
int n = wgt.size();
// Initialize dp table
vector<int> dp(cap + 1, 0);
// State transition
for (int i = 1; i <= n; i++) {
// Traverse in reverse order
for (int c = cap; c >= 1; c--) {
if (wgt[i - 1] <= c) {
// The greater value between not choosing and choosing item i
dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[cap];
}
/* Driver Code */
int main() {
vector<int> wgt = {10, 20, 30, 40, 50};
vector<int> val = {50, 120, 150, 210, 240};
int cap = 50;
int n = wgt.size();
// Brute force search
int res = knapsackDFS(wgt, val, n, cap);
cout << "The maximum value within the bag capacity is " << res << endl;
// Memoized search
vector<vector<int>> mem(n + 1, vector<int>(cap + 1, -1));
res = knapsackDFSMem(wgt, val, mem, n, cap);
cout << "The maximum value within the bag capacity is " << res << endl;
// Dynamic programming
res = knapsackDP(wgt, val, cap);
cout << "The maximum value within the bag capacity is " << res << endl;
// Space-optimized dynamic programming
res = knapsackDPComp(wgt, val, cap);
cout << "The maximum value within the bag capacity is " << res << endl;
return 0;
}