Description:

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).

Credits:
Special thanks to @Freezen for adding this problem and creating all test cases.

动态规划,有递推式:参考:http://blog.csdn.net/feliciafay/article/details/45128771

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])

public class Solution {
public int maxProfit(int k, int[] prices) { int len = prices.length; if(len < 2) {
return 0;
} if(k > len) {
return bigProfit(prices);
} int[] local = new int[k+1];
int[] global = new int[k+1]; Arrays.fill(local, 0);
Arrays.fill(global, 0); for(int i=0; i<len-1; i++) {
int diff = prices[i+1] - prices[i];
for(int j=k; j>=1; j--) {
local[j] = Math.max(global[j-1]+(diff>0?diff:0), local[j]+diff);
global[j] = Math.max(global[j], local[j]);
}
} return global[k];
} public int bigProfit(int[] prices) { int res = 0;
for(int i=0; i<prices.length-1; i++) {
if(prices[i] < prices[i+1]) {
res += prices[i+1] - prices[i];
}
} return res; } }

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