Say you have an array for which the i-th element is the price of a given stock on day i.
Design an algorithm to find the maximum profit. You may complete at most k transactions.
Note:
You may not engage in multiple transactions at the same time (ie, you must sell the stock before you buy again).
Example 1:
Input: [2,4,1], k = 2
Output: 2
Explanation: Buy on day 1 (price = 2) and sell on day 2 (price = 4), profit = 4-2 = 2.
Example 2:
Input: [3,2,6,5,0,3], k = 2
Output: 7
Explanation: Buy on day 2 (price = 2) and sell on day 3 (price = 6), profit = 6-2 = 4.
Then buy on day 5 (price = 0) and sell on day 6 (price = 3), profit = 3-0 = 3.
代码
Approach #1 Dynamic Programming
publicclassSolution {publicintmaxProfit(int k,int[] prices) {if (prices ==null||prices.length<=1|| k <=0) return0;// 1. Special caseint n =prices.length;if (k >= n /2) {int profit_max =0;for (int i =1; i < n; i++) {if (prices[i] - prices[i -1] >0) { profit_max += prices[i] - prices[i -1]; } }return profit_max; }// 2. dpint[][] f =newint[n +1][k +1];for (int j =1; j <= k; j++) {for (int i =1; i <= n; i++) {for (int x =0; x <= i; x++) { f[i][j] =Math.max(f[i][j], f[x][j -1] +profit(prices, x +1, i)); } } }return f[n][k]; }// [left, right]一次交易最大收益privateintprofit(int[] prices,int left,int right) {if (left >= right) return0;int leftMin =Integer.MAX_VALUE;int profit =0;for (int i = left; i < right; i++) { profit =Math.max(profit, prices[i] - leftMin); leftMin =Math.min(leftMin, prices[i]); }return profit; }}