LeetCode –Best Time to Buy and Sell Stock III
技术与社会生态的相互作用,使得技术发展经常带来更深远的问题,远远超出了技术设备的直接目的和运作本身,同样的技术,引入不同的环境,或在不同条件下,会带来非常不同的结果
题目描述
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 two transactions.
Note:
You may not engage in multiple transactions at the same time (ie, you must sell the stock before you buy again).
至多交易2次,求最大利益。
算法解释
- basically we want to maximize the formula: -price1 + price2 - price3 + price4, where every price appear in that order. So every time we visit a new price, we update the max possible value of 4 (partial) formula. That’s why we use max for each of the 4 states.
也就是状态机4个状态。和cooldown相似。
在每个步骤中,我们可以看到,oneBuy始终是输入数组中的最低价格,oneBuyOneSell跟踪价格和最低价格之间的最大差异,TwoBuy的价值变化反映了输入价格数组中的谷底。
变量TwoBuyTwoSell保持直到目前的价格的最大的利润,
(代码比较清晰易懂,请看代码)
- DP
f[k, ii] represents the max profit up until prices[ii] (Note: NOT ending with prices[ii]) using at most k transactions.
f[k, ii] = max(f[k, ii-1], prices[ii] - prices[jj] + f[k-1, jj]) { jj in range of [0, ii-1] }
= max(f[k, ii-1], prices[ii] + max(f[k-1, jj] - prices[jj]))
f[0, ii] = 0; 0 times transation makes 0 profit
f[k, 0] = 0; if there is only one price data point you can't make any money no matter how many times you can trade
状态转移方程明了了,解释略
代码
public int maxProfit(int[] prices) {
int oneBuy = Integer.MIN_VALUE;
int oneBuyOneSell = 0;
int twoBuy = Integer.MIN_VALUE;
int twoBuyTwoSell = 0;
for(int i = 0; i < prices.length; i++){
oneBuy = Math.max(oneBuy, -prices[i]);//we set prices to negative, so the calculation of profit will be convenient
oneBuyOneSell = Math.max(oneBuyOneSell, prices[i] + oneBuy);
twoBuy = Math.max(twoBuy, oneBuyOneSell - prices[i]);//we can buy the second only after first is sold
twoBuyTwoSell = Math.max(twoBuyTwoSell, twoBuy + prices[i]);
}
return Math.max(oneBuyOneSell, twoBuyTwoSell);
}
使用DP的方法
class Solution {
public:
int maxProfit(vector<int> &prices) {
if (prices.size() <= 1) return 0;
else {
int K = 2; // number of max transation allowed
int maxProf = 0;
vector<vector<int>> f(K+1, vector<int>(prices.size(), 0));
for (int kk = 1; kk <= K; kk++) {
int tmpMax = f[kk-1][0] - prices[0];
for (int ii = 1; ii < prices.size(); ii++) {
f[kk][ii] = max(f[kk][ii-1], prices[ii] + tmpMax);
tmpMax = max(tmpMax, f[kk-1][ii] - prices[ii]);
maxProf = max(f[kk][ii], maxProf);
}
}
return maxProf;
}
}
};