Codeforces 366C Dima and Salad 【dp】

本文介绍Codeforces366C题目的解决方案,通过将问题转化为0-1背包问题,利用动态规划求解最优解,实现找到满足特定条件的最大水果味道总和。

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题目链接:Codeforces 366C Dima and Salad
C. Dima and Salad
time limit per test1 second
memory limit per test256 megabytes
inputstandard input
outputstandard output
Dima, Inna and Seryozha have gathered in a room. That’s right, someone’s got to go. To cheer Seryozha up and inspire him to have a walk, Inna decided to cook something.

Dima and Seryozha have n fruits in the fridge. Each fruit has two parameters: the taste and the number of calories. Inna decided to make a fruit salad, so she wants to take some fruits from the fridge for it. Inna follows a certain principle as she chooses the fruits: the total taste to the total calories ratio of the chosen fruits must equal k. In other words, , where aj is the taste of the j-th chosen fruit and bj is its calories.

Inna hasn’t chosen the fruits yet, she is thinking: what is the maximum taste of the chosen fruits if she strictly follows her principle? Help Inna solve this culinary problem — now the happiness of a young couple is in your hands!

Inna loves Dima very much so she wants to make the salad from at least one fruit.

Input
The first line of the input contains two integers n, k (1 ≤ n ≤ 100, 1 ≤ k ≤ 10). The second line of the input contains n integers a1, a2, …, an (1 ≤ ai ≤ 100) — the fruits’ tastes. The third line of the input contains n integers b1, b2, …, bn (1 ≤ bi ≤ 100) — the fruits’ calories. Fruit number i has taste ai and calories bi.

Output
If there is no way Inna can choose the fruits for the salad, print in the single line number -1. Otherwise, print a single integer — the maximum possible sum of the taste values of the chosen fruits.

Examples
input
3 2
10 8 1
2 7 1
output
18
input
5 3
4 4 4 4 4
2 2 2 2 2
output
-1
Note
In the first test sample we can get the total taste of the fruits equal to 18 if we choose fruit number 1 and fruit number 2, then the total calories will equal 9. The condition fulfills, that’s exactly what Inna wants.

In the second test sample we cannot choose the fruits so as to follow Inna’s principle.

题意:从n个物品中选m个物品,要求 mi=1a[i]=kmi=1b[j] ,问最大的 mi=1a[i]

思路:转化问题,用容量为0的背包去装n个物品,物品重量为 a[i]b[i] 且价值为 a[i] ,要求装满背包且总价值最大。
dp[i][j] 表示前i个物品,总重量为j的最大价值。
dp[i][j]=max(dp[i1][j],dp[i1][ja[i]+kb[i]]+a[i])
由于j可以为负数,我们扩容M,求出的 dp[n][M] 就是结果。

AC代码:

#include <iostream>
#include <cstdio>
#include <cstring>
#include <cstdlib>
#include <cmath>
#include <algorithm>
#include <vector>
#include <queue>
#include <map>
#include <stack>
#define PI acos(-1.0)
#define CLR(a, b) memset(a, (b), sizeof(a))
#define fi first
#define se second
#define ll o<<1
#define rr o<<1|1
using namespace std;
typedef long long LL;
typedef pair<int, int> pii;
const int MAXN = 2*1e4 + 10;
const int pN = 1e6;// <= 10^7
const int INF = 0x3f3f3f3f;
const int MOD = 1e9 + 7;
void add(LL &x, LL y) { x += y; x %= MOD; }
pii a[110];
int dp[110][201000];
int N;
int main()
{
    int n, k; cin >> n >> k;
    for(int i = 1; i <= n; i++) {
        cin >> a[i].se;
    }
    N = n * 1000;
    for(int i = 1; i <= n; i++) {
        int b; cin >> b;
        a[i].fi = a[i].se - k * b;
    }
    CLR(dp, -INF); dp[0][N] = 0;
    for(int i = 1; i <= n; i++) {
        for(int j = 2*N; j >= a[i].fi; j--) {
            dp[i][j] = max(dp[i-1][j], dp[i-1][j-a[i].fi] + a[i].se);
        }
    }
    if(dp[n][N] <= 0) {
        cout << -1 << endl;
    }
    else {
        cout << dp[n][N] << endl;
    }
    return 0;
}
区间DP是一种动态规划的方法,用于解决区间范围内的问题。在Codeforces竞赛中,区间DP经常被用于解决一些复杂的字符串或序列相关的问题。 在区间DP中,dp[i][j]表示第一个序列前i个元素和第二个序列前j个元素的最优解。具体的转移方程会根据具体的问题而变化,但是通常会涉及到比较两个序列的元素是否相等,然后根据不同的情况进行状态转移。 对于区间长度为1的情况,可以先进行初始化,然后再通过枚举区间长度和区间左端点,计算出dp[i][j]的值。 以下是一个示例代码,展示了如何使用区间DP来解决一个字符串匹配的问题: #include <cstdio> #include <cstring> #include <string> #include <iostream> #include <algorithm> using namespace std; const int maxn=510; const int inf=0x3f3f3f3f; int n,dp[maxn][maxn]; char s[maxn]; int main() { scanf("%d", &n); scanf("%s", s + 1); for(int i = 1; i <= n; i++) dp[i][i] = 1; for(int i = 1; i <= n; i++) { if(s[i] == s[i - 1]) dp[i][i - 1] = 1; else dp[i][i - 1] = 2; } for(int len = 3; len <= n; len++) { int r; for(int l = 1; l + len - 1 <= n; l++) { r = l + len - 1; dp[l][r] = inf; if(s[l] == s[r]) dp[l][r] = min(dp[l + 1][r], dp[l][r - 1]); else { for(int k = l; k <= r; k++) { dp[l][r] = min(dp[l][r], dp[l][k] + dp[k + 1][r]); } } } } printf("%d\n", dp[n]); return 0; } 希望这个例子能帮助你理解区间DP的基本思想和应用方法。如果你还有其他问题,请随时提问。
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