最小生成树 prim

 Agri-Net

 POJ - 1258 

Farmer John has been elected mayor of his town! One of his campaign promises was to bring internet connectivity to all farms in the area. He needs your help, of course.
Farmer John ordered a high speed connection for his farm and is going to share his connectivity with the other farmers. To minimize cost, he wants to lay the minimum amount of optical fiber to connect his farm to all the other farms. 
Given a list of how much fiber it takes to connect each pair of farms, you must find the minimum amount of fiber needed to connect them all together. Each farm must connect to some other farm such that a packet can flow from any one farm to any other farm. 
The distance between any two farms will not exceed 100,000. 

Input

The input includes several cases. For each case, the first line contains the number of farms, N (3 <= N <= 100). The following lines contain the N x N conectivity matrix, where each element shows the distance from on farm to another. Logically, they are N lines of N space-separated integers. Physically, they are limited in length to 80 characters, so some lines continue onto others. Of course, the diagonal will be 0, since the distance from farm i to itself is not interesting for this problem.

Output

For each case, output a single integer length that is the sum of the minimum length of fiber required to connect the entire set of farms.

Sample Input

4
0 4 9 21
4 0 8 17
9 8 0 16
21 17 16 0

Sample Output

28

 

题意 : 简单来说 给n个点,给出 每两点之间的距离,然你算出来所有点之间最短的距离的和.

思路:小菜鸡第一次做最小生成树, 用 prim算法 跟迪杰斯特拉很想,唯一不同的是 更新的时候更新的是两点之间最短的距离,而不是从源点到该点的距离,每次找的都是最近的边存进dis数组里,然后加和,很像迪杰斯特拉,代码没什么差距,理解就好....

代码:

#include<stdio.h>
#include<algorithm>
#include<string.h>
using namespace std;
typedef long long ll;
const ll INF = 1000000000;
int n;
int d[10005];
int vis[10005];
int maze[105][105];

ll prim(){
    memset(d,INF,sizeof(d));
    memset(vis,0,sizeof(vis));
    for(int i = 1; i <= n; i++){
        d[i] = maze[1][i];//初始化
    }
    vis[1] = 1;
    int flag;
    ll sum = 0;
    for(int i = 2; i <= n; i ++){
        ll maxn = INF;
        for(int j = 1; j<= n;j++){
            if(!vis[j]&& maxn > d[j]){//找到 最短的边以及点.
                maxn = d[j];
                flag = j;
            }
        }
        vis[flag] = 1;
        sum += maxn;//将最短的距离求和
        for(int j = 1; j<= n; j++){
            if(!vis[j]){
                d[j] = min(d[j],maze[flag][j]);//更新该点与其相连的点之间的距离,只是该点与与它相连的点之间的距离而不是源点.
            }
        }

    }

    return sum;
}
int main()
{
    while(~scanf("%d",&n)){
        for(int i = 1; i <= n;i ++){
            for(int j = 1; j<= n;j ++){
                scanf("%d",&maze[i][j]);
            }
        }
        ll ans = prim();
        printf("%lld\n",ans);
    }
}
 

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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