HDU-6000

洗衣房调度算法

Wash

Time Limit: 20000/10000 MS (Java/Others)    Memory Limit: 64000/64000 K (Java/Others)
Total Submission(s): 2617    Accepted Submission(s): 703

 

Problem Description

Mr.Panda is about to engage in his favourite activity doing laundry! He’s brought L indistinguishable loads of laundry to his local laundromat, which has N washing machines and M dryers.The ith washing machine takes Wi minutes to wash one load of laundry, and the ith dryer takes Di minutes to dry a load of laundry.
At any point in time, each machine may only be processing at most one load of laundry.
As one might expect, Panda wants to wash and then dry each of his L loads of laundry. Each load of laundry will go through the following steps in order:
1. A non-negative amount of time after Panda arrives at the laundromat, Panda places the load in an unoccupied washing machine i.
2. Wi minutes later, he removes the load from the washing machine, placing it in a temporary holding basket (which has unlimited space)
3. A non-negative amount of time later, he places the load in an unoccupied dryer j
4. Dj minutes later, he removes the load from the dryer Panda can instantaneously add laundry to or remove laundry from a machine. Help Panda minimize the amount of time (in minutes after he arrives at the laundromat) after which he can be done washing and drying all L loads of laundry!

 

 

Input

The first line of the input gives the number of test cases, T.
T test cases follow. Each test case consists of three lines. The first line contains three integer L, N, and M.
The second line contains N integers W1,W2,...,WN representing the wash time of each wash machine.
The third line contains M integers D1,D2,...,DM representing the dry time of each dryer.

 

 

Output

For each test case, output one line containing “Case #x: y”, where x is the test case number (starting from 1) and y is the minimum time it will take Panda to finish his laundry.

limits


∙1≤T≤100 .
∙1≤L≤106 .
∙1≤N,M≤105 .
∙1≤Wi,Di≤109 .

 

 

Sample Input

2

1 1 1

1200

34

2 3 2

100 10 1

10 10

 

 

Sample Output

Case #1: 1234

Case #2: 12

解题思路:

看了好几篇博客终于理解了,洗衣服的过程很简单将输入的洗衣时间存入一个优先队列中,然后弹出第一个加上其对应的洗衣时间,继续放入队列。并用一个time数组记录每次洗完一件衣服的时间(烘干要用)。然后最难理解的就是烘干。要反过来思考,当你最后一件衣服洗完时,若能用到耗时最短的那个烘干机,那么总耗时一定最短(贪心思想来了),和洗衣服一样的道理,将每个烘干机的耗时存到一个优先队列中,每次弹出耗时最短的烘干机,烘干阶段time数组遍历时应该从后往前。让它与弹出的耗时最短的烘干机相加,将这个时间存到MAX中与下一次的比较。循环到下一次时两个时间作比较,依然保留最大的(而且是最优)。这样到最后一定是最优解。

先附上优先队列,结构体的模板:

#include <iostream>  
#include <cstdio>  
#include <vector>  
#include <queue>  
using namespace std;  

struct Node{  
    int x , y;  
    Node(int a = 0 , int b = 0){  
        x = a , y = b;  
    }  
};  

bool operator<(Node a , Node b){  
    if(a.x == b.x) return a.y>b.y;  
    return a.x>b.x;  
}  

int main(){  
    priority_queue<Node> q;  
    q.push(Node(0 , 1));  
    q.push(Node(1 , 1));  
    q.push(Node(1 , 2));  
    while(!q.empty()){  
        Node t = q.top();  
        q.pop();  
        cout << t.x<<" " << t.y << endl;  
    }  
    return 0;  
}  

AC代码:

#include<cstdio>
#include<iostream>
#include<queue>
using namespace std;
typedef long long int LL;
struct node {
    LL x;
    LL over_time;
};
bool operator<(node a, node b)
{
    return a.over_time > b.over_time;
}
LL a[1000010];

LL max1(LL x, LL y)
{
    if(x > y)
        return x;
    else
        return y;
}
int main()
{
    int T;
    struct node temp;
    int n, m, l;
    scanf("%d", &T);
    int num = 0;

    priority_queue<node> p;
    priority_queue<node> q;
    while(T--)
    {
        num++;
       while(!p.empty())
       {
           p.pop();
       }
       while(!q.empty())
       {
           q.pop();
       }
       scanf("%d%d%d", &l, &n, &m);
       for(int i = 0; i < n; ++i)
       {
           scanf("%lld", &temp.x);
           temp.over_time = temp.x;
           p.push(temp);
       }

        for(int i = 0; i < m; ++i)
       {
           scanf("%lld", &temp.x);
           temp.over_time = temp.x;
           q.push(temp);
       }

       for(int i = 0; i < l; ++i)
       {
          temp = p.top();
          a[i] = temp.over_time;
          temp.over_time += temp.x;
          p.pop();
          p.push(temp);
       }

       LL Max = -1;
       LL k;
       for(int i = l - 1; i >= 0; i--)
       {
            temp = q.top();
            k = temp.over_time + a[i];
            Max = max1(k, Max);
            temp.over_time = Max;
            q.push(temp);
       }
       printf("Case #%d: %lld\n", num, Max);
    }

}

 

### 关于HDU - 6609 的题目解析 由于当前未提供具体关于 HDU - 6609 题目的详细描述,以下是基于一般算法竞赛题型可能涉及的内容进行推测和解答。 #### 可能的题目背景 假设该题目属于动态规划类问题(类似于多重背包问题),其核心在于优化资源分配或路径选择。此类问题通常会给出一组物品及其属性(如重量、价值等)以及约束条件(如容量限制)。目标是最优地选取某些物品使得满足特定的目标函数[^2]。 #### 动态转移方程设计 如果此题确实是一个变种的背包问题,则可以采用如下状态定义方法: 设 `dp[i][j]` 表示前 i 种物品,在某种条件下达到 j 值时的最大收益或者最小代价。对于每一种新加入考虑范围内的物体 k ,更新规则可能是这样的形式: ```python for i in range(n): for s in range(V, w[k]-1, -1): dp[s] = max(dp[s], dp[s-w[k]] + v[k]) ``` 这里需要注意边界情况处理以及初始化设置合理值来保证计算准确性。 另外还有一种可能性就是它涉及到组合数学方面知识或者是图论最短路等相关知识点。如果是后者的话那么就需要构建相应的邻接表表示图形结构并通过Dijkstra/Bellman-Ford/Floyd-Warshall等经典算法求解两点间距离等问题了[^4]。 最后按照输出格式要求打印结果字符串"Case #X: Y"[^3]。 #### 示例代码片段 下面展示了一个简单的伪代码框架用于解决上述提到类型的DP问题: ```python def solve(): t=int(input()) res=[] cas=1 while(t>0): n,k=list(map(int,input().split())) # Initialize your data structures here ans=find_min_unhappiness() # Implement function find_min_unhappiness() res.append(f'Case #{cas}: {round(ans)}') cas+=1 t-=1 print("\n".join(res)) solve() ```
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