HDU - 4803 策略选择

本文介绍了一个关于仓库记录调整的问题,通过按钮操作改变屏幕上的数值,目标是最小化按钮按压次数来达到期望的显示结果。文章提供了一种解决策略及其实现代码。
Jenny is a warehouse keeper. He writes down the entry records everyday. The record is shown on a screen, as follow:

There are only two buttons on the screen. Pressing the button in the first line once increases the number on the first line by 1. The cost per unit remains untouched. For the screen above, after the button in the first line is pressed, the screen will be:

The exact total price is 7.5, but on the screen, only the integral part 7 is shown.
Pressing the button in the second line once increases the number on the second line by 1. The number in the first line remains untouched. For the screen above, after the button in the second line is pressed, the screen will be:

Remember the exact total price is 8.5, but on the screen, only the integral part 8 is shown.
A new record will be like the following:

At that moment, the total price is exact 1.0.
Jenny expects a final screen in form of:

Where x and y are previously given.
What’s the minimal number of pressing of buttons Jenny needs to achieve his goal?
Input
There are several (about 50, 000) test cases, please process till EOF.
Each test case contains one line with two integers x(1 <= x <= 10) and y(1 <= y <= 10 9) separated by a single space - the expected number shown on the screen in the end.
Output
For each test case, print the minimal number of pressing of the buttons, or “-1”(without quotes) if there’s no way to achieve his goal.
Sample Input
1 1
3 8
9 31
Sample Output
0
5
11


        
  
Hint
For the second test case, one way to achieve is:

(1, 1) -> (1, 2) -> (2, 4) -> (2, 5) -> (3, 7.5) -> (3, 8.5

把握的原则是,x加1对单价没什么影响,y加1才会提高单价,所以策略是先让y加,不能再加的时候让x加

ac代码:

#include <iostream>
#include <cstdio>
#include <algorithm>
#include <cstring>
#define esp 0.000001
using namespace std;

int main()
{
    int x,y;
    while(scanf("%d%d",&x,&y)!=EOF)
    {
        double i,j=1;
        double now=1;
        int step=0;
        int Max;
        for(i=1;i<=x;i++,step++)
        {
                j=now*i;
                if(j>=y&&j<y+1) break;
            for(;j<y+1;)
                {
                    Max=(y+1)*i/x-j-esp;
                    now=j/i;
                    if((j+1)/i*x>=y+1) break;
                    j+=Max;
                    step+=Max;
                    if(j>=y&&j<y+1) goto k;
                }
        }
        k:
        if(x>y) printf("-1\n");
        else
        printf("%d\n",step);
    }
    return 0;
}

HDU-3480 是一个典型的动态规划问题,其题目标题通常为 *Division*,主要涉及二维费用背包问题或优化后的动态规划策略。题目大意是:给定一个整数数组,将其划分为若干个连续的子集,每个子集最多包含 $ m $ 个元素,并且每个子集的最大值与最小值之差不能超过给定的阈值 $ t $,目标是使所有子集的划分代价总和最小。每个子集的代价是该子集最大值与最小值的差值。 ### 动态规划思路 设 $ dp[i] $ 表示前 $ i $ 个元素的最小代价。状态转移方程如下: $$ dp[i] = \min_{j=0}^{i-1} \left( dp[j] + cost(j+1, i) \right) $$ 其中 $ cost(j+1, i) $ 表示从第 $ j+1 $ 到第 $ i $ 个元素构成一个子集的代价,即 $ \max(a[j+1..i]) - \min(a[j+1..i]) $。 为了高效计算 $ cost(j+1, i) $,可以使用滑动窗口或单调队列等数据结构来维护区间最大值与最小值,从而将时间复杂度优化到可接受的范围。 ### 示例代码 以下是一个简化版本的动态规划实现,使用暴力方式计算区间代价,适用于理解问题结构: ```cpp #include <bits/stdc++.h> using namespace std; const int INF = 0x3f3f3f3f; const int MAXN = 10010; int a[MAXN]; int dp[MAXN]; int main() { int T, n, m; cin >> T; for (int Case = 1; Case <= T; ++Case) { cin >> n >> m; for (int i = 1; i <= n; ++i) cin >> a[i]; dp[0] = 0; for (int i = 1; i <= n; ++i) { dp[i] = INF; int mn = a[i], mx = a[i]; for (int j = i; j >= max(1, i - m + 1); --j) { mn = min(mn, a[j]); mx = max(mx, a[j]); if (mx - mn <= T) { dp[i] = min(dp[i], dp[j - 1] + mx - mn); } } } cout << "Case " << Case << ": " << dp[n] << endl; } return 0; } ``` ### 优化策略 - **单调队列**:可以使用两个单调队列分别维护当前窗口的最大值与最小值,从而将区间代价计算的时间复杂度从 $ O(n^2) $ 降低到 $ O(n) $。 - **斜率优化**:若问题满足特定的决策单调性,可以考虑使用斜率优化技巧进一步加速状态转移过程。 ### 时间复杂度分析 原始暴力解法的时间复杂度为 $ O(n^2) $,在 $ n \leq 10^4 $ 的情况下可能勉强通过。通过单调队列优化后,可以稳定运行于 $ O(n) $ 或 $ O(n \log n) $。 ### 应用场景 HDU-3480 的问题模型可以应用于资源调度、任务划分等场景,尤其适用于需要控制子集内部差异的问题,如图像分块压缩、数据分段处理等[^1]。 ---
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