hello-algo/en/codes/dart/chapter_dynamic_programming/unbounded_knapsack.dart

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1.8 KiB
Dart

/**
* File: unbounded_knapsack.dart
* Created Time: 2023-08-11
* Author: liuyuxin (gvenusleo@gmail.com)
*/
import 'dart:math';
/* Complete knapsack: Dynamic programming */
int unboundedKnapsackDP(List<int> wgt, List<int> val, int cap) {
int n = wgt.length;
// Initialize dp table
List<List<int>> dp = List.generate(n + 1, (index) => List.filled(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][c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[n][cap];
}
/* Complete knapsack: Space-optimized dynamic programming */
int unboundedKnapsackDPComp(List<int> wgt, List<int> val, int cap) {
int n = wgt.length;
// Initialize dp table
List<int> dp = List.filled(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[c] = dp[c];
} else {
// 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 */
void main() {
List<int> wgt = [1, 2, 3];
List<int> val = [5, 11, 15];
int cap = 4;
// Dynamic programming
int res = unboundedKnapsackDP(wgt, val, cap);
print("Maximum value of items without exceeding bag capacity = $res");
// Space-optimized dynamic programming
int resComp = unboundedKnapsackDPComp(wgt, val, cap);
print("Maximum value of items without exceeding bag capacity = $resComp");
}