forked from JiauZhang/algorithms
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy path2_knapsack_acwing.cpp
119 lines (100 loc) · 3.46 KB
/
2_knapsack_acwing.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
/*
* Copyright(c) 2019 Jiau Zhang
* For more information see <https://github.com/JiauZhang/algorithms>
*
* This repo is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation
*
* It is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with THIS repo. If not, see <http://www.gnu.org/licenses/>.
*/
#include <iostream>
/*
完全背包问题
*/
using namespace std;
int knapsack_2d(int N, int V, int v[], int w[])
{
int dp[N+1][V+1] = {0};
/* 必须自己初始化,定义处无法实现清零操作 */
for (int i=0; i<=N; i++) dp[i][0] = 0;
for (int i=0; i<=V; i++) dp[0][i] = 0;
for (int i=1; i<=N; i++) {
for (int j=1; j<=V; j++) {
/* 不选第 i 个的情况 */
dp[i][j] = dp[i-1][j];
int iter = j / v[i];
/* 选择第 i 个 k 次 */
for (int k=1; k<=iter; k++) {
/* 这个 if 就没必要了,因为 k 已经限制了这种可能 */
//if (v[i] <= j) {
dp[i][j] = max(dp[i][j], dp[i-1][j-k*v[i]]+k*w[i]);
//}
}
}
}
return dp[N][V];
}
int knapsack_1d_v1(int N, int V, int v[], int w[])
{
int dp[V+1] = {0};
for (int i=1; i<=N; i++) {
for (int j=V; j>=1; j--) {
int iter = j / v[i];
for (int k=1; k<=iter; k++) {
// if (v[i] <= j) {
dp[j] = max(dp[j], dp[j-k*v[i]]+k*w[i]);
// }
}
}
}
return dp[V];
}
/*
v2 算法分析
区别于 0-1 背包问题,现在可以无限次选
f[i][j] --> -->
当选第 i 件物品时,选择次数有 0, 1, 2, ..., k 且 k*v[i] <= j
对应的总价值分别涉及到 f[i-1][j], f[i-1][j-v[i]], f[i-1][j-2*v[i]], ..., f[i-1][j-k*v[i]]
分析对应的行中索引值 j, j-v[i], j-2*v[i], ..., j-k*v[i]
由于 k*v[i] <= j,所以索引值范围是 j 到 0 之间的数据
当 dp 表降维为 一维时,涉及到的总价值为 f[j], f[j-v[i]], f[j-2*v[i]], ..., f[j-k*v[i]]
同样的,此时涉及的索引值范围是 j 到 0 之间的数据,即从当前点到 0 之间的数据
当我们使用 v1 版本时,从右到左 更新正是出于这个原因
dp 长度对应的是不同容量,即从 0, 1, 2, ..., V
现在已知的是,由于是一维 dp,所以当我们不取第 i 个物品时,当前价值就等于当前值,不需要更新
假设现在物品容量为 v[i], 则容量从 0,1, ..., v[i]-1 之间数据都保持不变,因为背包容量不够用
当容量为 v[i] 时,这时就有了两种情况:取和不取
即每次涉及到取和不取是以 v[i] 为间隔出现的,其中0, v[i], 2*v[i], ..., V记录的就是第 i 个
物品在总容量为 V 的情况下取不同次数的 总价值
*/
int knapsack_1d_v2(int N, int V, int v[], int w[])
{
int dp[V+1] = {0};
for (int i=1; i<=N; i++) {
for (int j=v[i]; j<=V; j++) {
dp[j] = max(dp[j], dp[j-v[i]]+w[i]);
}
}
return dp[V];
}
int main()
{
int N, V;
cin>>N>>V;
int v[N+1], w[N+1];
v[0] = w[0] = 0;
for (int i=1; i<=N; i++)
cin>>v[i]>>w[i];
// int res = knapsack_1d_v1(N, V, v, w);
int res = knapsack_1d_v2(N, V, v, w);
// int res = knapsack_2d(N, V, v, w);
cout << res;
return 0;
}