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.
Swift DSA Implementation
basic.swift
func rowString(_ row: [Int]) -> String {
"[" + row.map(String.init).joined(separator: ", ") + "]"
}
func tableString(_ table: [[Int]]) -> String {
"[" + table.map(rowString).joined(separator: ", ") + "]"
}
let weights = [2, 3, 4, 5]
let values = [3, 4, 5, 6]
let capacity = 5
var dp = Array(repeating: Array(repeating: 0, count: capacity + 1), count: weights.count + 1)
for item in 1...weights.count {
let weight = weights[item - 1]
let value = values[item - 1]
for cap in 0...capacity {
if weight > cap {
dp[item][cap] = dp[item - 1][cap]
} else {
let skip = dp[item - 1][cap]
let take = value + dp[item - 1][cap - weight]
dp[item][cap] = max(skip, take)
}
}
}
print(dp[weights.count][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