HDU5491 The Next

本文介绍了一种算法,用于解决特定的编程竞赛问题:找到比给定数字d大的最小WHYnumber,即其二进制中1的数量位于[s1, s2]区间内。通过调整d的二进制表示,确保新数的1位数符合要求。

题目链接:http://acm.hdu.edu.cn/showproblem.php?pid=5491


题意:一个数对应的二进制的1的个数在[ s1 , s2 ]内,则称为WHY number。

给定一个数字d为WHY number,求比d大的最小的WHY number(即下一个)


思路:先计算出d的二进制中含有1的个数,如果小于上限d2且d是偶数,则答案为d+1。

否则加上lowbit(d),由于加上后1的个数只减不增,故不会出现num1>d2的情况。

若此时符合条件,即为答案。否则补上不足的1(s1-num1),即2^(s1-num1)-1


code:

#include<cstdio>
using namespace std;
typedef long long ll;
ll lowbit(ll x)
{
    return x&-x;
}
ll num1(ll x)
{
    ll res=0;
    while(x)
    {
        if(x&1)
        res++;
        x/=2;
    }
    return res;
}
int main()
{
    int T,cas=1;
    scanf("%d",&T);
    while(T--)
    {
        ll x,s1,s2;
        scanf("%lld%lld%lld",&x,&s1,&s2);
        if((x&1)==0&&s2>num1(x)) x++;
        else
        {
            x+=lowbit(x);
            ll t=num1(x);
            if(t<s1) x+=(1<<(s1-t))-1;
        }
        printf("Case #%d: %lld\n",cas++,x);
    }
    return 0;
}


### HDU 1466 Problem Description and Solution The problem **HDU 1466** involves calculating the expected number of steps to reach a certain state under specific conditions. The key elements include: #### Problem Statement Given an interactive scenario where operations are performed on numbers modulo \(998244353\), one must determine the expected number of steps required to achieve a particular outcome. For this type of problem, dynamic programming (DP) is often employed as it allows breaking down complex problems into simpler subproblems that can be solved iteratively or recursively with memoization techniques[^1]. In more detail, consider the constraints provided by similar problems such as those found in references like HDU 6327 which deals with random sequences using DP within given bounds \((1 \leq T \leq 10, 4 \leq n \leq 100)\)[^2]. These types of constraints suggest iterative approaches over small ranges might work efficiently here too. Additionally, when dealing with large inputs up to \(2 \times 10^7\) as seen in reference materials related to counting algorithms [^4], efficient data structures and optimization strategies become crucial for performance reasons. However, directly applying these methods requires understanding how they fit specifically into solving the expectation value calculation involved in HDU 1466. For instance, if each step has multiple outcomes weighted differently based on probabilities, then summing products of probability times cost across all possible states until convergence gives us our answer. To implement this approach effectively: ```python MOD = 998244353 def solve_expectation(n): dp = [0] * (n + 1) # Base case initialization depending upon problem specifics for i in range(1, n + 1): total_prob = 0 # Calculate transition probabilities from previous states for j in transitions_from(i): # Placeholder function representing valid moves prob = calculate_probability(j) next_state_cost = get_next_state_cost(j) dp[i] += prob * (next_state_cost + dp[j]) % MOD total_prob += prob dp[i] %= MOD # Normalize current state's expectation due to accumulated probability mass if total_prob != 0: dp[i] *= pow(total_prob, MOD - 2, MOD) dp[i] %= MOD return dp[n] # Example usage would depend heavily on exact rules governing transitions between states. ``` This code snippet outlines a generic framework tailored towards computing expectations via dynamic programming while adhering strictly to modular arithmetic requirements specified by the contest question format.
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