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hello-algo/codes/go/chapter_dynamic_programming/unbounded_knapsack.go

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// File: unbounded_knapsack.go
// Created Time: 2023-07-23
// Author: Reanon (793584285@qq.com)
package chapter_dynamic_programming
import "math"
/* 完全背包:动态规划 */
func unboundedKnapsackDP(wgt, val []int, cap int) int {
n := len(wgt)
// 初始化 dp 表
dp := make([][]int, n+1)
for i := 0; i <= n; i++ {
dp[i] = make([]int, cap+1)
}
// 状态转移
for i := 1; i <= n; i++ {
for c := 1; c <= cap; c++ {
if wgt[i-1] > c {
// 若超过背包容量,则不选物品 i
dp[i][c] = dp[i-1][c]
} else {
// 不选和选物品 i 这两种方案的较大值
dp[i][c] = int(math.Max(float64(dp[i-1][c]), float64(dp[i][c-wgt[i-1]]+val[i-1])))
}
}
}
return dp[n][cap]
}
/* 完全背包:空间优化后的动态规划 */
func unboundedKnapsackDPComp(wgt, val []int, cap int) int {
n := len(wgt)
// 初始化 dp 表
dp := make([]int, cap+1)
// 状态转移
for i := 1; i <= n; i++ {
for c := 1; c <= cap; c++ {
if wgt[i-1] > c {
// 若超过背包容量,则不选物品 i
dp[c] = dp[c]
} else {
// 不选和选物品 i 这两种方案的较大值
dp[c] = int(math.Max(float64(dp[c]), float64(dp[c-wgt[i-1]]+val[i-1])))
}
}
}
return dp[cap]
}