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).
[balabala] 自己的想法是先找出收益最大的一笔收益,然后从剩余区间中寻找次大的收益,但是在一些case上会失败,比如 [6,1,3,2,4,7]。为什么这种贪婪做法得不到全局最优解呢?如yb君指点,因为第一次交易确定会影响第二次交易的可选范围,子问题之间相互影响,所以不可用最优子问题叠加获取最优解。
正确的思路:至多能做两笔交易,而且交易之间没有重叠,想到可以用divide and conque. 如yb君说,需要综合使用多种算法的题目就会显得比较难。这题就是分治 + 动归 综合题。
public class Solution {
// 以每一天为分界点,分别求出左边和右边能获得的最大收益,然后求出最大值
// 分治 + 动归
public int maxProfit(int[] prices) {
if (prices == null || prices.length < 2)
return 0;
int[] left = new int[prices.length];
int low = prices[0];
int maxleft = 0;
for (int i = 0; i < prices.length; i++) {
left[i] = Math.max(maxleft, prices[i] - low);
low = Math.min(low, prices[i]);
}
int[] right = new int[prices.length];
int high = prices[prices.length - 1];
int maxright = 0;
for (int i = prices.length - 1; i >=0 ;i--) {
right[i] = Math.max(maxright, high - prices[i]);
high = Math.max(high, prices[i]);
}
int maxprofit = 0;
for (int i = 0; i < prices.length; i++) {
maxprofit = Math.max(maxprofit, left[i] + right[i]);
}
}
////////////////////////////////下面为不正确思路的实现//////////////////////////////
//fail @ [6,1,3,2,4,7]
class ProfitInfo {
int buyDay;
int sellDay;
int profit;
public ProfitInfo(int buyDay, int sellDay, int profit) {
this.buyDay = buyDay;
this.sellDay = sellDay;
this.profit = profit;
}
}
public int maxProfit(int[] prices) {
if (prices == null || prices.length < 2)
return 0;
ProfitInfo profit1 = maxProfit(prices, 0, prices.length - 1);
ProfitInfo profit2 = maxProfit(prices, 0, profit1.buyDay - 1);
ProfitInfo profit3 = maxProfit(prices, profit1.sellDay + 1, prices.length - 1);
return profit1.profit + Math.max(profit2.profit, profit3.profit);
}
private ProfitInfo maxProfit(int[] prices, int start, int end) {
if (start >= end) // length of range <= 1
return new ProfitInfo(start, end, 0);
int min = start;
int buy = start;
int profit = 0;
int sell = start;
for (int i = start + 1; i <= end; i++) {
if (prices[i] < prices[min]) {
min = i;
} else if (prices[i] > prices[min]){
int currProfit = prices[i] - prices[min];
if (currProfit >= profit) {
profit = currProfit;
buy = min;
sell = i;
}
}
}
return new ProfitInfo(buy, sell, profit);
}
// fail @ [2, 4, 1] buy不能同时承担最小价格日以及当前最大profit的购买日,两者不一定是同一个值
private ProfitInfo maxProfit(int[] prices, int start, int end) {
if (start >= end) // length of range <= 1
return new ProfitInfo(start, end, 0);
int buy = start;
int profit = 0;
int sell = start;
for (int i = start + 1; i <= end; i++) {
if (prices[i] < prices[buy]) {
buy = i;
} else if (prices[i] > prices[buy]){
int currProfit = prices[i] - prices[buy];
if (currProfit >= profit) {
profit = currProfit;
sell = i;
}
}
}
return new ProfitInfo(buy, sell, profit);
}
}

本文探讨了给定股票价格数组,如何设计算法找到最多进行两次交易以获得最大利润的方法。通过分治与动态规划结合的方式解决了问题,并给出了具体的Java代码实现。
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