Recursion and Dynamic Programming
0/1 Knapsack (Small)
Fill a small 0/1 knapsack table where each row decides whether one more item is available.
Algorithm
@steps
- Create a table with one extra row for using zero items.
- Process the four items in fixed order.
- For each capacity, inherit when the item is too heavy.
- Otherwise compare
skipandtakefrom the previous row. - Print the best value and the full deterministic table. @end @complexity
- Time: O(item_count * capacity)
- Space: O(item_count * capacity) @end
state transition
`dp[i][w]` compares skipping item `i` with taking it and reading the remaining capacity from the previous row.
Dart DSA Implementation
basic.dart
String rowString(List<int> row) => "[${row.join(", ")}]";
String tableString(List<List<int>> table) => "[${table.map(rowString).join(", ")}]";
void main() {
final weights = [2, 3, 4, 5];
final values = [3, 4, 5, 6];
const capacity = 5;
final dp = List.generate(weights.length + 1, (_) => List<int>.filled(capacity + 1, 0));
for (var item = 1; item <= weights.length; item++) {
final weight = weights[item - 1];
final value = values[item - 1];
for (var cap = 0; cap <= capacity; cap++) {
if (weight > cap) {
dp[item][cap] = dp[item - 1][cap];
} else {
final skip = dp[item - 1][cap];
final take = value + dp[item - 1][cap - weight];
dp[item][cap] = skip > take ? skip : take;
}
}
}
print(dp[weights.length][capacity]);
print(tableString(dp));
}
@end @output 7 [[0, 0, 0, 0, 0, 0], [0, 0, 3, 3, 3, 3], [0, 0, 3, 4, 4, 7], [0, 0, 3, 4, 5, 7], [0, 0, 3, 4, 5, 7]] @end