【CodeForces 55D】Beautiful number 数位DP

本文提供了一个针对 CodeForces-55D 问题的解决方案,通过数字DP技术实现,能够处理高达9 * 10^18 的数值范围。文章包含完整的代码实现及注释说明,适用于解决涉及数字枚举和限制条件下的计数问题。

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Problem

https://vjudge.net/problem/CodeForces-55D

Solution

http://blog.youkuaiyun.com/lhq_er/article/details/77017024
代码更新过了,这个链接里的只能做到 1018 ,这个能到 91018

CODE

/*
 * @key words: digit DP
 * @tested on: CF 55D 1058ms
 * @Author: LuHaoqi 
 * @Date: 2017-08-11 17:22:47 
 * @Last Modified by: LuHaoqi
 * @Last Modified time: 2017-08-11 17:42:48
 */
#include<cstdio>
#include<iostream>
#include<algorithm>
#include<cmath>
#include<cstring>
using namespace std;
#define ll long long
ll pow10[22],Pow[22],dp[22][2][2520][50];
int num[22],flcm[512],Map[2521],Map2[50],tmp[22],tot;

int gcd(int a,int b)
{
    return b==0?a:gcd(b,a%b);
}
int lcm(int a,int b)
{
    if (a==0) return b;
    else if (b==0) return a;
    else return a/gcd(a,b)*b;
}
ll solve(ll x)
{
    int len=0;
    ll ans=0;
    while (x) tmp[++len]=x%10,x/=10;
    for (int i=1;i<=len;i++) num[i]=tmp[len-i+1];
    memset(dp,0,sizeof(dp));
    dp[0][1][0][0]=1;
    for (int i=0;i<=len;i++)
        for (int j=0;j<2;j++)
            for (int k=0;k<2520;k++)
                for (int l=0;l<tot;l++)
                {
                    ll p=dp[i][j][k][l];
                    int pp=Map2[l];
                    if (!p) continue;
                    if (i==len) 
                    {
                        if (k % pp==0) ans+=p;
                        continue;
                    }
                    if (j==0)
                    {
                        for (int q=0;q<=9;q++)
                            dp[i+1][0][(k+q*Pow[len-i-1])%2520][Map[lcm(pp,q)]]+=p;                     
                    }
                    else
                    {
                        for (int q=0;q<num[i+1];q++)
                            dp[i+1][0][(k+q*Pow[len-i-1])%2520][Map[lcm(pp,q)]]+=p;
                        dp[i+1][1][(k+num[i+1]*Pow[len-i-1])%2520][Map[lcm(pp,num[i+1])]]+=p;
                    }               
                }
    return ans;
}
void prepare()
{
    pow10[0]=Pow[0]=1;
    for (int i=1;i<=18;i++) pow10[i]=pow10[i-1]*10,Pow[i]=pow10[i]%2520;
    for (int i=1;i<(1<<9);i++)
        for (int j=1;j<=9;j++)
            if (i & (1<<j-1))
                flcm[i]=lcm(flcm[i-(1<<j-1)],j);
    for (int i=1;i<(1<<9);i++)
        if (!Map[flcm[i]]) Map[flcm[i]]=tot++,Map2[tot-1]=flcm[i];
}
int main()
{
    prepare();
    int T;
    scanf("%d",&T);
    while (T--)
    {
        ll a,b;
        cin>>a>>b;
        cout<<solve(b)-solve(a-1)<<endl;
    }   
    return 0;
}
### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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