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[leecode]Best Time to Buy and Sell Stock III

Best Time to Buy and Sell Stock III

Say you have an array for which the ith element is the price of a given stock on day i.

Design an algorithm to find the maximum profit. You may complete at most two transactions.

Note:
You may not engage in multiple transactions at the same time (ie, you must sell the stock before you buy again).

算法分析:

DP+二分:

正向遍历,用一个一维数组left[i]表示0 ~ i 的最大收益

逆向遍历,用一个一维数组right[i] 表示 i ~ length - 1的最大收益

最后求出最大的left[i] + right[i]

对于点j+1,求price[0..j+1]的最大profit时,很多工作是重复的,在求price[0..j]的最大profit中已经做过了。
类似于Best Time to Buy and Sell Stock,可以在O(1)的时间从price[0..j]推出price[0..j+1]的最大profit。
但是如何从price[j..n-1]推出price[j+1..n-1]?反过来思考,我们可以用O(1)的时间由price[j+1..n-1]推出price[j..n-1]。
最终算法:
数组l[i]记录了price[0..i]的最大profit,
数组r[i]记录了price[i..n]的最大profit。
已知l[i],求l[i+1]是简单的,同样已知r[i],求r[i-1]也很容易。
最后,我们再用O(n)的时间找出最大的l[i]+r[i],即为题目所求。

代码如下:

 1 public class Solution { 2     public int maxProfit(int[] prices) { 3         if(prices == null || prices.length < 2) return 0; 4         int length = prices.length; 5         int[] left = new int[length]; 6         int[] right = new int[length]; 7         int buyIn = prices[0],sellOut = prices[length - 1]; 8         for(int i = 1; i < length; i++){ 9             left[i] = Math.max(left[i - 1], prices[i] - buyIn);10             buyIn = Math.min(prices[i],buyIn);11         }12         for(int i = length - 2; i >= 0; i--){13             right[i] = Math.max(right[i + 1], sellOut - prices[i]);14             sellOut = Math.max(prices[i],sellOut);15         }16         int res = 0;17         for(int i = 0; i < length; i++){18             res = Math.max(res, left[i] + right[i]);19         }20         return res;21     }22 }

 

[leecode]Best Time to Buy and Sell Stock III