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 (i.e., you must sell the stock before you buy again).
Example 1:
Input: [3,3,5,0,0,3,1,4]
Output: 6
Explanation: Buy on day 4 (price = 0) and sell on day 6 (price = 3), profit = 3-0 = 3.
Then buy on day 7 (price = 1) and sell on day 8 (price = 4), profit = 4-1 = 3.
Example 2:
Input: [1,2,3,4,5]
Output: 4
Explanation: Buy on day 1 (price = 1) and sell on day 5 (price = 5), profit = 5-1 = 4.
Note that you cannot buy on day 1, buy on day 2 and sell them later, as you are
engaging multiple transactions at the same time. You must sell before buying again.
Example 3:
Input: [7,6,4,3,1]
Output: 0
Explanation: In this case, no transaction is done, i.e. max profit = 0.
classSolution {publicintmaxProfit(int price[],int i,int n,int K,int dp[][][],int ongoing) {// Base casesif (i == n)return0;if (K ==0) { dp[i][K][ongoing] =0;return0; }if (dp[i][K][ongoing] !=-1)return dp[i][K][ongoing];int ans =maxProfit(price, i +1, n, K, dp, ongoing);if (ongoing ==1) {int option =maxProfit(price, i +1, n, K -1, dp,0)+ price[i]; ans =Math.max(ans, option); } else {int option =maxProfit(price, i +1, n, K, dp,1)- price[i]; ans =Math.max(ans, option); } dp[i][K][ongoing] = ans;return ans; }publicintmaxProfit(int[] prices) {int n =prices.length;int dp[][][] =newint[n +1][2+1][2];for (int i =0; i <= n; i++) {for (int j =0; j <=2; j++) { dp[i][j][0] =-1; dp[i][j][1] =-1; } }returnmaxProfit(prices,0, n,2, dp,0); }}