codeforces 863E

本文介绍了一种解决区间覆盖问题的有效算法。通过先对区间进行排序,再逐一判断哪些区间可以被其他区间覆盖,从而找出可以删除的区间。文章提供了一个完整的C++实现示例。

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原题链接

我的思路:

这是一条不难的题目,我直接先按左边优先排序,如果左边相同,就按右边排序。

按这样的排序方案排序后,我们来一条条地加边。首先第1条肯定是需要的。对于第2条,假设 l1.rl2.r ,又由于 l1.ll2.l ,那么此时第2条就是可以删除的边,因为第2条边干的活第1条边都干了,此时找到答案,结束;如果 l1.r<l2.r ,那么 l2 此时对于整体是有贡献的,贡献是 [max(l1.r+1, l2.l), l2.r] 部分,因此此时需要修改 l2.l 。此时看第3条边,假设 l2.rl3.r ,注意,此时虽然已经修改了 l2.l ,但是覆盖的部分并不会减少,只是多做出贡献的部分减少了,此时 l3 就是一条没有用的边,找到了答案,退出;否则,此时修改 l3.l 。然后一直继续下去。

#include <iostream>
#include <algorithm>

using namespace std;

const int maxn = 2e5 +10;
typedef struct Node{
    int l, r;
    int pos;
    bool operator < (const Node & R) const
    {
        if(l != R.l) return l < R.l;
        return r < R.r;
    }
}Node;
Node s[maxn];
int main() {
    int t;
    cin >> t;
    for(int i = 0; i < t; i++) {
        int l, r;
        cin >> s[i].l >> s[i].r;
        s[i].pos = i + 1;
    }
    sort(s, s + t);
    int ans = -1;
    for(int i = 1; i < t; i++) {
        if(s[i - 1].r >= s[i].r) {
            ans = s[i].pos;
            break;
        } else if(s[i - 1].l >= s[i].l) {
            ans = s[i - 1].pos;
            break;
        }
        s[i].l = max(s[i].l, s[i - 1].r + 1);
    }
    cout << ans << endl;
    return 0;
}
### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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