awesome-go/impl/algorithms/dynamic_programming dynamic_programming dynamic_programming dynamic_programming/KnapsackProblem.go

47 lines
992 B
Go

package main
import "fmt"
type Item struct {
value, weight int
}
func knapsack(items []Item, capacity int) int {
n := len(items)
// Create a memoization table
memo := make([][]int, n+1)
for i := range memo {
memo[i] = make([]int, capacity+1)
}
// Fill the memoization table using dynamic programming
for i := 1; i <= n; i++ {
for w := 1; w <= capacity; w++ {
if items[i-1].weight <= w {
memo[i][w] = max(items[i-1].value+memo[i-1][w-items[i-1].weight], memo[i-1][w])
} else {
memo[i][w] = memo[i-1][w]
}
}
}
return memo[n][capacity]
}
func max(a, b int) int {
if a > b {
return a
}
return b
}
func main() {
items := []Item{
{value: 60, weight: 10},
{value: 100, weight: 20},
{value: 120, weight: 30},
}
capacity := 50
fmt.Printf("Maximum value: %d\n", knapsack(items, capacity))
}