我一直在尝试解决这个HackerEarth问题,但最后几个测试用例似乎总是超时
我是一年级学生,所以我真的不知道如何更好地优化它
我尝试查看java解决方案,但它只是将较大的情况放入代码中,有效地消除了对其进行优化的需要。
import java.io.*;
import java.util.*;
public class police {
static int t,n,k;
static char[][] test;
static int max = 0;
public static void main(String[] args) throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
StringTokenizer st = new StringTokenizer(br.readLine());
t = Integer.parseInt(st.nextToken());
for (int i = 0; i < t; i++) {
st = new StringTokenizer(br.readLine());
n = Integer.parseInt(st.nextToken());
k = Integer.parseInt(st.nextToken());
test = new char[n][n];
int ret = 0;
for (int b = 0; b < n; b++) {
st = new StringTokenizer(br.readLine());
for (int a = 0; a < n; a++) {
test[b][a] = st.nextToken().charAt(0);
}
}
for (int b = 0; b < n; b++) {
ret += solve(test[b]); //calculate each row
}
System.out.println(ret);
}
}
static int solve(char[] a) { //given a row, calculate the maximum number of catches
int ret = 0;
for (int i = 0; i < n; i++) {
if (a[i] == 'P') {
for (int b = i - k; b <= i + k; b++) { //scan area to see if police can catch a thief
if (b >= 0 && b < n && a[b] == 'T') {
a[b] = 'C'; //caught
break;
}
}
a[i] = 'U'; //used
}
}
for (int i = 0; i < n; i++) //count
if (a[i] == 'C')
ret++;
return ret;
}
}我很确定这与solve方法有关,如果有人能帮助我,那就太棒了
发布于 2018-12-22 12:13:07
您是对的,您在solve方法中使用的方法是导致超时的原因。
首先,您需要对algorithm complexity和Big O notation有一个概念
问题的约束是:
1 <= N <= 1000
1 <= K <= N * N
这表明您的解决方案的复杂性最高应该是O(N * N)。换句话说,至多嵌套两个for循环,每个循环的复杂度为O(N)。
在您的解决方案中,您将执行以下操作:
for (int b = 0; b < n; b++) {
ret += solve(test[b]); //calculate each row
}好的,这个循环是必不可少的,因为你必须遍历网格中的所有行。复杂性:O(N)
然后在你的solve方法中:
for (int i = 0; i < n; i++) {
if (a[i] == 'P') {
for (int b = i - k; b <= i + k; b++) { //scan area to see if police can catch a thief
if (b >= 0 && b < n && a[b] == 'T') {
a[b] = 'C'; //caught
break;
}
}
a[i] = 'U'; //used
}
}这些嵌套的for循环才是问题的真正原因,对于较高的K值,外部循环的复杂度是O(N),而内部循环的复杂度也可能是O(N)。因此,这三个for循环的总复杂度可能会达到O(N * N * N),这肯定会超时。
这是我对这个问题的解决方案,我只修改了solve方法:
static int solve(char[] a) { //given a row, calculate the maximum number of catches
int ret = 0;
ArrayDeque<Integer> policeMenQueue = new ArrayDeque<>(); // queue for holding positions of policemen
ArrayDeque<Integer> thievesQueue = new ArrayDeque<>(); // queue for positions of thieves
for (int i = 0; i < n; i++) {
if(!policeMenQueue.isEmpty()) { // check if the leftmost policeman can catch a thief at current position (i)
Integer mostLeftPoliceMan = policeMenQueue.getFirst();
if(i - mostLeftPoliceMan > k) { // if he cannot then we must remove him as he will no longer be able to catch any thieves
policeMenQueue.removeFirst();
}
}
if(!thievesQueue.isEmpty()) { // check if the leftmost thief can be caught be a policeman at current position (i)
Integer mostLeftThief = thievesQueue.getFirst();
if(i - mostLeftThief > k) { // if not then we must remove him as he will no longer be caught by any policemen
thievesQueue.removeFirst();
}
}
if(a[i] == 'P') {
if(!thievesQueue.isEmpty()) { // the leftmost thief can be caught by current policeman
ret++;
thievesQueue.removeFirst(); // ok this thief is caught, remove him
} else {
policeMenQueue.addLast(i); // just add the policeman to keep his position in the queue
}
}
if(a[i] == 'T') {
if(!policeMenQueue.isEmpty()) { // the current thief can be caught by the leftmost policeman
ret++;
policeMenQueue.removeFirst(); // ok this policeman has already caught a thief (used), remove him
} else {
thievesQueue.addLast(i); // just add the thief to keep his position in the queue
}
}
}
return ret;
}我的想法是:从左到右循环每一行,正如问题所述:每个警察只能抓到一个小偷,我们想要最大限度地增加被抓小偷的数量,所以每个小偷都被最左边的警察抓住是对我们有利的(因为我们从左到右)。
例如,考虑以下行:
P P T T
想象一下K = 2
我们希望3位置的小偷被1位置的警察抓住,因为这个警察不能抓住4位置的小偷,当然在这种情况下2位置的警察可以抓住两个小偷,但请记住,我们必须最大限度地增加被抓小偷的数量,每个警察只能抓住一个小偷,所以我们希望每个小偷都被能够抓住他的最左边的警察抓住。
我的解决方案依赖于queue数据结构(Java中的ArrayDeque),如果你不知道它是如何工作的,或者我为什么要使用它,可以看看这里:https://www.tutorialspoint.com/data_structures_algorithms/dsa_queue.htm
https://stackoverflow.com/questions/53892027
复制相似问题