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 as many transactions as you like (ie, buy one and sell one share of the stock multiple times) with the following restrictions:
You may not engage in multiple transactions at the same time (ie, you must sell the stock before you buy again).
After you sell your stock, you cannot buy stock on next day. (ie, cooldown 1 day)
Example:
prices = [1, 2, 3, 0, 2]
maxProfit = 3
transactions = [buy, sell, cooldown, buy, sell]
Credits:
Special thanks to @dietpepsi for adding this problem and creating all test cases.
自己的思路很烂,一个我觉得最好懂的Share my DP solution (By State Machine Thinking)
附上代码
public class Solution {
public int maxProfit(int[] prices) {
if(prices==null||prices.length==0) return 0;
int[] s0 = new int[prices.length];
int[] s1 = new int[prices.length];
int[] s2 = new int[prices.length];
s0[0] = 0;
s1[0] = -prices[0];
s2[0] = Integer.MIN_VALUE;
for(int i=1; i<prices.length; i++){
s0[i] = Math.max(s0[i-1], s2[i-1]);
s1[i] = Math.max(s1[i-1], s0[i-1] - prices[i]);
s2[i] = s1[i-1] + prices[i];
}
return Math.max(s0[prices.length-1], s2[prices.length-1]);
}
}
本文介绍了一种股票交易算法的设计,该算法允许多次买卖操作并遵循特定的限制条件,如冷却期等。通过状态机思考的方式,利用动态规划求解最大利润。
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