POJ 3126 Prime Path (BFS)

本文介绍了一个有趣的算法问题:寻找两个四数位素数之间的最便宜转换路径,通过改变一位数字来移动到另一个素数,同时确保每一步都是素数。使用广度优先搜索(BFS)算法解决此问题,并详细解释了实现过程。

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The ministers of the cabinet were quite upset by the message from the Chief of Security stating that they would all have to change the four-digit room numbers on their offices.
— It is a matter of security to change such things every now and then, to keep the enemy in the dark.
— But look, I have chosen my number 1033 for good reasons. I am the Prime minister, you know!
— I know, so therefore your new number 8179 is also a prime. You will just have to paste four new digits over the four old ones on your office door.
— No, it’s not that simple. Suppose that I change the first digit to an 8, then the number will read 8033 which is not a prime!
— I see, being the prime minister you cannot stand having a non-prime number on your door even for a few seconds.
— Correct! So I must invent a scheme for going from 1033 to 8179 by a path of prime numbers where only one digit is changed from one prime to the next prime.

Now, the minister of finance, who had been eavesdropping, intervened.
— No unnecessary expenditure, please! I happen to know that the price of a digit is one pound.
— Hmm, in that case I need a computer program to minimize the cost. You don't know some very cheap software gurus, do you?
— In fact, I do. You see, there is this programming contest going on... Help the prime minister to find the cheapest prime path between any two given four-digit primes! The first digit must be nonzero, of course. Here is a solution in the case above.

1033
1733
3733
3739
3779
8779
8179
The cost of this solution is 6 pounds. Note that the digit 1 which got pasted over in step 2 can not be reused in the last step – a new 1 must be purchased.

Input
One line with a positive number: the number of test cases (at most 100). Then for each test case, one line with two numbers separated by a blank. Both numbers are four-digit primes (without leading zeros).
Output
One line for each case, either with a number stating the minimal cost or containing the word Impossible.
Sample Input
3
1033 8179
1373 8017
1033 1033
Sample Output
6
7
0

  

BFS,判断素数可以提前素数筛打表也可以跑从1到sqrt(n)的循环,因为只是四位数所以肯定不会TLE。


入队方式我是开了方向数组,把每一位分别+(-9,-8,-7...-1,1,...8,9)然后看改动后是否合法。


改完的数要保证是四位数并且只改了一位,没有退位和进位。


剩下和普通BFS一样,存步数即可。



#include<stdio.h>
#include<stdlib.h>
#include<string.h>
#include<math.h>
#include<queue>
#include<map>
#include<algorithm>
#include<iostream>
#define ll long long
#define ull long long
const int N=1e9+7;
const int M=1e6+5;
using namespace std;

int i,j,k,n,m;
int c[20]={-9,-8,-7,-6,-5,-4,-3,-2,-1,1,2,3,4,5,6,7,8,9};   //每一位的数字可以加这些数
int d[10005]; // 标记数组

struct node
{
    int x;
    int y;
};

bool check1(int x)  //判断是不是素数
{
    bool flag=true;
    for(int i=2;i*i<=x;i++)
    {
       if(x%i==0)
       {
           flag=false;
           break;
       }
    }
    return flag;
}

bool check2(int x)  //判断是否合法
{
    return x>=1000&&x<=9999&&!d[x];
}

int bfs() // 广搜
{
    int e,f,z;
    memset(d,0,sizeof(d));
    queue<node>q;
    node a,b;
    a.x=n,a.y=0;
    q.push(a);
    d[n]=1;
    while(!q.empty())
    {
        a=q.front();
        q.pop();
        for(i=0;i<4;i++)
        {
            if(i==0) e=1;             //个位改动
            if(i==1) e=10;           //十位改动
            if(i==2) e=100;        //百位改动
            if(i==3) e=1000;      //千位改动
            for(j=0;j<18;j++)
            {
                f=a.x+e*c[j];
                z=a.x%(e*10)+e*c[j];
                if(z>=e*10||z<0) continue;  // 如果改动以后数据不是四位数 或者导致改动的位数超过一位  则不合法
                if(check1(f)&&check2(f))
                {
                    b.x=f;
                    b.y=a.y+1;
                    if(b.x==m) return b.y;
                    d[f]=1;
                    q.push(b);
                }
            }
        }
    }
}

int main()
{
    int T;
    scanf("%d",&T);
    while(T--)
    {
        scanf("%d%d",&n,&m);
        if(n==m)  //特判
        {
            printf("0\n");
            continue;
        }
        int ans=bfs();
        printf("%d\n",ans);
    }
    return 0;
}
内容概要:该论文探讨了一种基于粒子群优化(PSO)的STAR-RIS辅助NOMA无线通信网络优化方法。STAR-RIS作为一种新型可重构智能表面,能同时反射和传输信号,与传统仅能反射的RIS不同。结合NOMA技术,STAR-RIS可以提升覆盖范围、用户容量和频谱效率。针对STAR-RIS元素众多导致获取完整信道状态信息(CSI)开销大的问题,作者提出一种在不依赖完整CSI的情况下,联合优化功率分配、基站波束成形以及STAR-RIS的传输和反射波束成形向量的方法,以最大化总可实现速率并确保每个用户的最低速率要求。仿真结果显示,该方案优于STAR-RIS辅助的OMA系统。 适合人群:具备一定无线通信理论基础、对智能反射面技术和非正交多址接入技术感兴趣的科研人员和工程师。 使用场景及目标:①适用于希望深入了解STAR-RIS与NOMA结合的研究者;②为解决无线通信中频谱资源紧张、提高系统性能提供新的思路和技术手段;③帮助理解PSO算法在无线通信优化问题中的应用。 其他说明:文中提供了详细的Python代码实现,涵盖系统参数设置、信道建模、速率计算、目标函数定义、约束条件设定、主优化函数设计及结果可视化等环节,便于读者理解和复现实验结果。此外,文章还对比了PSO与其他优化算法(如DDPG)的区别,强调了PSO在不需要显式CSI估计方面的优势。
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