hdu Moving Tables

本文介绍了一个关于桌子在特定走廊布局中高效搬运的问题。通过分析不同搬运路径间的交叉情况,提出了一个算法来确定最小化总搬运时间的方法。

Moving Tables

Time Limit : 2000/1000ms (Java/Other)   Memory Limit : 65536/32768K (Java/Other)
Total Submission(s) : 51   Accepted Submission(s) : 24
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Problem Description

The famous ACM (Advanced Computer Maker) Company has rented a floor of a building whose shape is in the following figure.



The floor has 200 rooms each on the north side and south side along the corridor. Recently the Company made a plan to reform its system. The reform includes moving a lot of tables between rooms. Because the corridor is narrow and all the tables are big, only one table can pass through the corridor. Some plan is needed to make the moving efficient. The manager figured out the following plan: Moving a table from a room to another room can be done within 10 minutes. When moving a table from room i to room j, the part of the corridor between the front of room i and the front of room j is used. So, during each 10 minutes, several moving between two rooms not sharing the same part of the corridor will be done simultaneously. To make it clear the manager illustrated the possible cases and impossible cases of simultaneous moving.



For each room, at most one table will be either moved in or moved out. Now, the manager seeks out a method to minimize the time to move all the tables. Your job is to write a program to solve the manager’s problem.

Input

The input consists of T test cases. The number of test cases ) (T is given in the first line of the input. Each test case begins with a line containing an integer N , 1<=N<=200 , that represents the number of tables to move. Each of the following N lines contains two positive integers s and t, representing that a table is to move from room number s to room number t (each room number appears at most once in the N lines). From the N+3-rd line, the remaining test cases are listed in the same manner as above.

Output

The output should contain the minimum time in minutes to complete the moving, one per line.

Sample Input

3 
4 
10 20 
30 40 
50 60 
70 80 
2 
1 3 
2 200 
3 
10 100 
20 80 
30 50 

Sample Output

10

20

30

题目大意:人们从不同的房间搬桌子到不同的房间,对于每个人来说不管路多长都只用十分钟搬完。计算所有人都搬完桌子共用多少时间。

解题思路:如果人们搬桌子的路径没有交叉的话,那总时间就是十分钟,如果有路径被公用的话,并且其中有一段被共用的次数最多,那么该段路径每有一个人经过就得用十分钟,所以总时间便是最繁忙的那段路径的次数乘十即为总时间。

代码:

#include <iostream>
using namespace std;
int main()
{
    int m,n,i,j,k,l,s,p;
    int b[500];
    cin>>n;
    while(n--)
    {
        memset(b,0,sizeof(b));
        cin>>m;
        for(i=0;i<m;i++)
        {
             cin>>s>>p;
             if(s>p)
                 swap(s,p);
             s=(s+1)/2;//因为房间是两个相对的所以只找一半就可以了
             p=(p+1)/2;
             for(j=s;j<=p;j++)
             {
                 b[j]++;//记录每段路径的繁忙度
             }
        }
        int max=0;//找最繁忙的路径
        for(i=1;i<=202;i++)
        {
             if(b[i]>max)
             {
                  max=b[i];
             }
        }
       
        cout<<max*10<<endl;
    }
    return 0;
}

 

内容概要:本文系统介绍了算术优化算法(AOA)的基本原理、核心思想及Python实现方法,并通过图像分割的实际案例展示了其应用价值。AOA是一种基于种群的元启发式算法,其核心思想来源于四则运算,利用乘除运算进行全局勘探,加减运算进行局部开发,通过数学优化器加速函数(MOA)和数学优化概率(MOP)动态控制搜索过程,在全局探索与局部开发之间实现平衡。文章详细解析了算法的初始化、勘探与开发阶段的更新策略,并提供了完整的Python代码实现,结合Rastrigin函数进行测试验证。进一步地,以Flask框架搭建前后端分离系统,将AOA应用于图像分割任务,展示了其在实际工程中的可行性与高效性。最后,通过收敛速度、寻优精度等指标评估算法性能,并提出自适应参数调整、模型优化和并行计算等改进策略。; 适合人群:具备一定Python编程基础和优化算法基础知识的高校学生、科研人员及工程技术人员,尤其适合从事人工智能、图像处理、智能优化等领域的从业者;; 使用场景及目标:①理解元启发式算法的设计思想与实现机制;②掌握AOA在函数优化、图像分割等实际问题中的建模与求解方法;③学习如何将优化算法集成到Web系统中实现工程化应用;④为算法性能评估与改进提供实践参考; 阅读建议:建议读者结合代码逐行调试,深入理解算法流程中MOA与MOP的作用机制,尝试在不同测试函数上运行算法以观察性能差异,并可进一步扩展图像分割模块,引入更复杂的预处理或后处理技术以提升分割效果。
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