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“最大子序列和”算法 java

maxSubSum分别是最大子序列和的4中java算法实现。

第一种算法运行时间为O(N^3),第二种算法运行时间为O(N^2),第三种算法运行时间为O(nlogn),第四种算法运行时间为线性N


public class Test {
	public static void main(String[] args) {
		int[] a = {-2, 11, -4, 13, -5, -2};//最大子序列和为20
		int[] b = {-6, 2, 4, -7, 5, 3, 2, -1, 6, -9, 10, -2};//最大子序列和为16
		System.out.println(maxSubSum4(a));
		System.out.println(maxSubSum4(b));
	}
	//最大子序列求和算法一
	public static int maxSubSum1(int[] a){
		
		int maxSum = 0;
		
		//从第i个开始找最大子序列和
		for(int i = 0; i < a.length; i++) {
			
			//找第i到j的最大子序列和
			for(int j = i; j<a.length; j++) {
				
				int thisSum = 0;
				
				//计算从第i个开始,到第j个的和thisSum
				for(int k = i; k<=j; k++){
					thisSum += a[k];
				}
				//如果第i到第j个的和小于thisSum,则将thisSum赋值给maxSum
				if(thisSum>maxSum) {
					maxSum = thisSum;
				}
			}
		}
		return maxSum;
	}
	
	public static int maxSubSum2(int[] a) {
		int maxSum = 0;
		for(int i = 0; i < a.length; i++) {
			//将sumMax放在for循环外面,避免j的变化引起i到j的和sumMax要用for循环重新计算
			int sumMax = 0;
			for(int j = i; j < a.length; j++) {
				sumMax += a[j];
				if(sumMax>maxSum) {
					maxSum = sumMax;
				}
			}
		}
		return maxSum;
	}
	
	//递归,分治策略
	//2分logn,for循环n,固O(nlogn)
	public static int maxSubSum3(int[] a) {
		return maxSumRec(a, 0, a.length - 1);
	}
	public static int maxSumRec(int[] a, int left, int right) {
		//递归中的基本情况
		if(left == right) {
			if(a[left] > 0) return a[left];
			else return 0;
		} 
		int center = (left + right) / 2;
		//最大子序列在左侧
		int maxLeftSum = maxSumRec(a, left, center);
		//最大子序列在右侧
		int maxRightSum = maxSumRec(a, center+1, right);
		//最大子序列在中间(左边靠近中间的最大子序列+右边靠近中间的最大子序列)
		int maxLeftBorderSum = 0, leftBorderSum = 0;
		for(int i = center; i>=left; i--) {
			leftBorderSum += a[i];
			if(leftBorderSum > maxLeftBorderSum) maxLeftBorderSum = leftBorderSum;
		}
		int maxRightBorderSum = 0, rightBorderSum = 0;
		for(int i = center+1; i<= right; i++) {
			rightBorderSum += a[i];
			if(rightBorderSum > maxRightBorderSum) maxRightBorderSum = rightBorderSum;
		}
		//返回最大子序列在左侧,在右侧,在中间求出的值中的最大的
		return max3(maxLeftSum, maxRightSum, maxLeftBorderSum + maxRightBorderSum);
	}
	public static int max3(int a, int b, int c) {
		return a > b?(a>c?a:c):(b>c?b:c);
	}
	//任何a[i]为负时,均不可能作为最大子序列前缀;任何负的子序列不可能是最有子序列的前缀
	public static int maxSubSum4 (int [] a) {
		int maxSum = 0, thisSum = 0;
		for(int j = 0; j < a.length; j++) {
			thisSum += a[j];
			if(thisSum>maxSum) maxSum = thisSum;
			else if (thisSum < 0) thisSum = 0; 
		}
		return maxSum;
	}
}