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.
121, 123题的延伸版本,123题是只交易2次,本题是交易k次
思路:
虽然整体思路和123题一样,但是不能直接那样做,因为在k很大的时候,比如k=100亿次,这时候声明的dp数组会超出内存,所以需要在123题的基础上做一些优化
需要知道的是一次有收益的交易最少是需要2天完成的,当天买当天卖肯定没有收益。
那么就算是不停地交易,当天买第二天就卖掉,也只需要prices.length/2次
所以当k>=prices.length/2时,不需要真的计算k次,只需要用贪心法算出最大的收益
就是每当第二天价格>当天价格的时候就加到收益里面,直接返回最大收益
然后k < prices.length/2时,就按照123题的dp来做:
第 i 次交易时, j 时刻如果选择不交易,收益是保持第i次,j-1时刻的收益,也就是dp[i][j - 1]
如果选择在j时刻卖掉,因为买入可以是从0到j-1的任何一个,设m=0~j-1
那么收益就是第i-1次交易时,m时刻的收益,减去买入m时刻的价格,加上现在在j时刻卖掉的价格,即
dp[i-1][m] - prices[m] + prices[j], for m = 0~ j - 1
要在m=0~j-1中取最大收益
max(dp[i-1][m] - prices[m] ) + prices[j], for m = 0~ j - 1
不需要在每个j时都遍历0~j-1,只需要保持实时更新最大差值即可
要在交易和不交易两种情况中取较大的值
dp[i][j] = max(dp[i][j - 1], max_diff + prices[j])
int maxProfit(int k, vector<int>& prices) {
if (k == 0 || prices.size() == 0) {
return 0;
}
int max_profit = 0;
if (k >= prices.size()/2) {
for (int i = 1; i < prices.size(); i++) {
if (prices[i] > prices[i - 1]) {
max_profit += (prices[i] - prices[i - 1]);
}
}
return max_profit;
}
vector<vector<int>> dp(k + 1, vector<int>(prices.size(), 0));
for (int i = 1; i <= k; i++) {
int max_diff = -prices[0];
for (int j = 1; j < prices.size(); j++) {
dp[i][j] = max(dp[i][j - 1], max_diff + prices[j]);
max_diff = max(max_diff, dp[i - 1][j] - prices[j]);
}
}
return dp[k][prices.size() - 1];
}
java版本
public int maxProfit(int k, int[] prices) {
if(k == 0 || prices.length == 0) {
return 0;
}
int n = prices.length;
//int[][] dp = new int[k+1][n]; //写在这里会MLE
int result = 0;
//k >= n/2时为greedy
if(k >= n/2) {
for(int i = 1; i < n; i++) {
int val = prices[i] - prices[i - 1];
if(val > 0) {
result += val;
}
}
return result;
}
int[][] dp = new int[k+1][n];
//ith transaction:max profit in 0~m, buy at m, sell at j,m:0~j-1
//for m: dp[i][j] = max(dp[i-1][m] - prices[m]) + prices[j]
//dp[i][j]:第i次transaction,在j时间点处的profit
//不交易时保持在第i次transaction,j-1时间点处的profit(第i行必须是第i次transaction)
for(int i = 1; i <= k; i++) {
int maxDiff = -prices[0];
for(int j = 1; j < n; j++) {
dp[i][j] = Math.max(dp[i][j-1], maxDiff + prices[j]);
maxDiff = Math.max(maxDiff, dp[i-1][j] - prices[j]);
}
}
return dp[k][n-1];
}