PTA:Maximum Subsequence Sum

最新推荐文章于 2021-10-07 21:22:21 发布

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最新推荐文章于 2021-10-07 21:22:21 发布

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本文深入探讨了求解最大子序列和的经典算法，通过详细分析输入规格和输出规格，展示了如何高效地从一系列整数中找出具有最大和的连续子序列。特别关注了特殊情况的处理，如所有数均为负数时的定义，并提供了完整的C++实现代码。

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Input Specification:
Each input file contains one test case. Each case occupies two lines. The first line contains a positive integer K (≤10000). The second line contains K numbers, separated by a space.

Output Specification:
For each test case, output in one line the largest sum, together with the first and the last numbers of the maximum subsequence. The numbers must be separated by one space, but there must be no extra space at the end of a line. In case that the maximum subsequence is not unique, output the one with the smallest indices i and j (as shown by the sample case). If all the K numbers are negative, then its maximum sum is defined to be 0, and you are supposed to output the first and the last numbers of the whole sequence.

Sample Input:
10
-10 1 2 3 4 -5 -23 3 7 -21
Sample Output:
10 1 4

#include <bits/stdc++.h>
using namespace std;

int main()
{
	int N;
	cin >> N;
	int array[N];
	for (int i = 0; i < N; i++) {
		cin >> array[i];
	}
	int sum=0,first=0,src=N-1,end=N-1,max=-1;

	for (int i = 0; i < N; i++) {
		sum += array[i];
		if (sum > max) {
			max = sum;
			src = first;
			end = i;
		}

		if (sum <0) {
			first = i + 1;
			sum = 0;
		}
	}
	if (max<0) cout << 0 << ' ' << array[0] << ' ' << array[N - 1];
	else cout << max << ' ' << array[src] << ' ' << array[end];
    return 0;
}