Description
有两个正整数数列,元素个数分别为N和M。从两个数列中分别任取一个数相乘,这样一共可以得到N*M个数,询问这N*M个数中第K小数是多少。
Input
输入文件包含三行。
第一行为三个正整数N,M和K。
第二行为N个正整数,表示第一个数列。
第三行为M个正整数,表述第二个数列。
Output
输出文件包含一行,一个正整数表示第K小数。
Sample Input
Sample1:
2 3 4
1 2
2 1 3
Sample2:
5 5 18
7 2 3 5 8
3 1 3 2 5
Data Constraint
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" 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" alt=" " />
二分答案$\large mid$, 问题转化成判断是否有$\large k$个数<=mid。
显然不能$\large n^{2}$判断, 不然还不如枚举然后排序。
所以我们先把$\large a$,$\large b$数组从小到大排序。
然后枚举$\large a$的数位置$\large i$, 我们发现当$\large i$递增的时候,满足$\large a[i]*b[j]<=mid$的j的位置一定是单调递减的。
所以我们可以保留$\large j$在上次的位置继续判断。
复杂度$\large O(Nlog(maxnum))$可过。
#include <iostream>
#include <cstdio>
#include <algorithm>
using namespace std;
#define reg register
#define ll long long
inline ll read() {
ll res=;char ch=getchar();
while(!isdigit(ch))ch=getchar();
while(isdigit(ch))res=(res<<)+(res<<)+(ch^), ch=getchar();
return res;
}
int n, m;
ll k, ans, sum;
ll a[], b[];
inline bool check(ll mid)
{
ll j = m;
for (reg ll i = ; i <= n ; i ++)
{
while (a[i] * b[j] > mid) j --;
sum += j;
}
if (sum >= k) return ;
return ;
}
signed main()
{
n = read(), m = read();
scanf("%lld", &k);
for (reg int i = ; i <= n ; i ++) a[i] = read();
for (reg int i = ; i <= m ; i ++) b[i] = read();
sort (a + , a + + n);
sort (b + , b + + m);
ll l = , r = a[n] * b[m];
while (l <= r)
{
ll mid = l + r >> ;
sum = ;
if (check(mid)) r = mid - , ans = mid;
else l = mid + ;
}
printf("%lld\n", ans);
return ;
}
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