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 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.
- Method 1: dp
- We need to pay attention to the initialization.
- Transaction function is same as 123. Best Time to Buy and Sell Stock III.
- If k is larger than prices length, we treat it as question 122. Best Time to Buy and Sell Stock II.
class Solution { public int maxProfit(int k, int[] prices) { if(k == 0 || prices == null || prices.length <= 1) return 0; int len = prices.length; if(k > len) return maxProfit(prices); int[][] buys = new int[len + 1][k + 1]; int[][] sells = new int[len + 1][k + 1]; for(int i = 2; i <= k; i++){ for(int j = 0; j < i; j++){ buys[j][i] = Integer.MIN_VALUE; } } int sum = 0; for(int i = 1; i <= k; i++){ sum -= prices[i - 1]; buys[i][i] = sum; } for(int i = 2; i <= len; i++){ for(int j = 1; j <= k; j++){ buys[i][j] = Math.max(buys[i - 1][j], sells[i - 1][j - 1] - prices[i - 1]); sells[i][j] = Math.max(sells[i - 1][j], buys[i - 1][j] + prices[i - 1]); } } int profit = 0; for(int i = 0; i <= k; i++){ profit = Math.max(profit, sells[len][i]); } return profit; } private int maxProfit(int[] prices) { int len = prices.length; int[] buys = new int[len + 1]; int[] sells = new int[len + 1]; buys[1] = -prices[0]; for(int i = 2; i <= len; i++){ buys[i] = Math.max(buys[i - 1], sells[i - 1] - prices[i - 1]); sells[i] = Math.max(sells[i - 1], buys[i - 1] + prices[i - 1]); } return sells[len]; } }