求数组中连续n个元素使其和最大

本文介绍了一种寻找数组中连续元素最大和的算法,并提供了五种不同实现方式,包括从O(n^3)到O(n)的时间复杂度优化过程。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

      给定一个数组,求出数组中连续的一些元素使其和的值最大。如果所有元素都为正数,显然整个数组即为所求的。如果所有元素的值为负数,则所求的最大值为0.

      这是在编程珠玑上看到的,其时间复杂度由O(n3)减为O(n)了。

 

public class MaxSum 
{
	public static void main(String[] args)
	{
		int[] arr = new int[]{31, -41, 59, 26, -53, -58, -97, -93, -23, -84};
		
		MaxSum ms = new MaxSum();
		
		ms.Max(arr);
		ms.Max2(arr);
		ms.Max3(arr);
		
		int max = ms.Max4(arr, 0, arr.length-1);
		System.out.println("Max sum is " + max);
		
		ms.Max5(arr);
	}
	
	//方法1: 时间复杂度为O(n*n*n)
	public void Max(int[] arr)
	{
		int max = 0;
		int sum = 0;
		int left = -1;
		int right = -1;
		
		for(int i=0; i<arr.length; i++)
		{
			for(int j=i; j<arr.length; j++)
			{
				sum = 0;
				
				for(int k=i; k<=j; k++)
				{
					sum = sum + arr[k];
				}
				
				if(sum > max)
				{
					left = i;
					right = j;
					max = sum;
				}
			}
		}
		
		if(right > 0)
		{
			System.out.println("Max is from element " + left + "(" + arr[left] + ") to element " + right + "(" + arr[right] + "), max sum is " + max);
		}
		else if(right == 0)
		{
			System.out.println("Max sum is " + arr[0]);
		}
		else
		{
			System.out.println("Max sum is 0 .");
		}
	}
	
	//方法2:时间复杂度为O(n*n)
	public void Max2(int[] arr)
	{
		int max = 0;
		int sum = 0;
		int left = -1;
		int right = -1;
		
		for(int i=0; i<arr.length; i++)
		{
			sum = 0;
			for(int j=i; j<arr.length; j++)
			{
				sum = sum + arr[j];
				if(sum > max)
				{
					left = i;
					right = j;
					max = sum;
				}
			}
		}
		
		if(right > 0)
		{
			System.out.println("Max is from element " + left + "(" + arr[left] + ") to element " + right + "(" + arr[right] + "), max sum is " + max);
		}
		else if(right == 0)
		{
			System.out.println("Max sum is " + arr[0]);
		}
		else
		{
			System.out.println("Max sum is 0 .");
		}
	}
	
	//方法3:时间复杂度为O(n*n)
	public void Max3(int[] arr)
	{
		int max = 0;
		int sum = 0;
		int left = -1;
		int right = -1;
		
		int[] temp = new int[arr.length+1];
		
		temp[0] = 0;
		for(int i=0; i<arr.length; i++)
		{
			temp[i+1] = temp[i] + arr[i];
		}
		
		for(int i=0; i<arr.length; i++)
		{
			for(int j=i; j<temp.length; j++)
			{
				sum = temp[j] - temp[i];
				if(sum > max)
				{
					left = i;
					right = j-1;
					max = sum;
				}
			}
		}
		
		if(right > 0)
		{
			System.out.println("Max is from element " + left + "(" + arr[left] + ") to element " + right + "(" + arr[right] + "), max sum is " + max);
		}
		else if(right == 0)
		{
			System.out.println("Max sum is " + arr[0]);
		}
		else
		{
			System.out.println("Max sum is 0 .");
		}
	}
	
	//方法4:时间复杂度为O(n*logn)
	public int Max4(int[] arr, int left, int right)
	{
		int sum = 0;
		int max = 0;
		int max1 = 0;
		int max2 = 0;
		int middle = 0;
		
		if(left > right)
		{
			return 0;
		}
		else if(left == right)
		{
			return (arr[left] > 0 ? arr[left] : 0);
		}
		
		middle = (left + right)/2;
		
		for(int i=middle; i>=left; i--)
		{
			sum = sum + arr[i];
			if(sum > max1)
			{
				max1 = sum;
			}
		}
		
		sum=0;
		for(int i=middle+1; i<=right; i++)
		{
			sum = sum + arr[i];
			if(sum > max2)
			{
				max2 = sum;
			}
		}
		
		max = max1+max2;
		int temp1 = Max4(arr, left, middle);
		int temp2 = Max4(arr, middle+1, right);
		
		if(temp1 > max)
		{
			max = temp1;
		}
		
		if(temp2 > max)
		{
			max = temp2;
		}
		
		return max;
	}
	
	//方法5:时间复杂度为O(n)
	public void Max5(int[] arr)
	{
		int max1 = 0;
		int max2 = 0;
		int left = -1;
		int right = -1;
		int temp = 0;
		int count = 0;
		
		for(int i=0; i<arr.length; i++)
		{
			temp = (max1+arr[i]);
			if(temp > 0)
			{
				count++;
				
				if(count == 1)
					left = i;
				
				max1 = temp;
				
				if(max1 > max2)
				{
					right = i;
					max2 = max1;
				}
			}
			else
			{
				max1 = 0;
				count = 0;
			}

			
		}
		
		if(right > 0)
		{
			System.out.println("Max is from element " + left + "(" + arr[left] + ") to element " + right + "(" + arr[right] + "), max sum is " + max2);
		}
		else if(right == 0)
		{
			System.out.println("Max sum is " + arr[0]);
		}
		else
		{
			System.out.println("Max sum is 0 .");
		}
	}
}

 

 

输出为:

Max is from element 2(59) to element 3(26), max sum is 85
Max is from element 2(59) to element 3(26), max sum is 85
Max is from element 2(59) to element 3(26), max sum is 85
Max sum is 85
Max is from element 2(59) to element 3(26), max sum is 85

 

 

评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值