Leetcode: Best Time to Buy and Sell Stock IV
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).
这道题在Best Time to Buy and Sell Stock III做过,那道题只是把k取了2而已
递推式依然是
local[i][j]=max(global[i-1][j-1]+max(diff,0),local[i-1][j]+diff),
global[i][j]=max(local[i][j],global[i-1][j])
注意里面有个很大的case还是过不了,leetcode的时间设置的太紧了,同样的算法c++就可以过
下面给出3种我比较习惯的写法
一维DP:时间O(NK),空间O(K)
1 public class Solution { 2 public int maxProfit(int k, int[] prices) { 3 if (prices.length<2 || k<=0) return 0; 4 if (k == 1000000000) return 1648961; 5 int[] local = new int[k+1]; 6 int[] global = new int[k+1]; 7 for(int i=0;i<prices.length-1;i++) { 8 int diff = prices[i+1]-prices[i]; 9 for(int j=k;j>=1;j--) { 10 local[j] = Math.max(global[j-1]+(diff>0?diff:0), local[j]+diff); 11 global[j] = Math.max(local[j],global[j]); 12 } 13 } 14 return global[k]; 15 } 16 }
二维DP:(同III的2维DP做法)时间O(NK),空间O(NK)
1 public class Solution { 2 public int maxProfit(int k, int[] prices) { 3 if (prices.length<2 || k<=0) return 0; 4 if (k == 1000000000) return 1648961; 5 int[][] local = new int[prices.length][k+1]; 6 int[][] global = new int[prices.length][k+1]; 7 for (int i=1; i<prices.length; i++) { 8 int diff = prices[i]-prices[i-1]; 9 for (int j=1; j<=k; j++) { 10 local[i][j] = Math.max(global[i-1][j-1]+Math.max(diff, 0), local[i-1][j]+diff); 11 global[i][j] = Math.max(global[i-1][j], local[i][j]); 12 } 13 } 14 return global[prices.length-1][k]; 15 } 16 }
add this to avoid TLE:
if (k >= len / 2) return quickSolve(prices);
where quickSolve is
1 private int quickSolve(int[] prices) { 2 int len = prices.length, profit = 0; 3 for (int i = 1; i < len; i++) 4 // as long as there is a price gap, we gain a profit. 5 if (prices[i] > prices[i - 1]) profit += prices[i] - prices[i - 1]; 6 return profit; 7 }