Say you have an array for which the ith element is the price of a given stock on day i.
If you were only permitted to complete at most one transaction (ie, buy one and sell one share of the stock), design an algorithm to find the maximum profit.
思路:买和卖的时间必然是先买后卖,所以倒着搜索,可以用O(N)的复杂度实现。
class Solution {
public:
int maxProfit(vector<int> &prices) {
// Start typing your C/C++ solution below
// DO NOT write int main() function
int n = prices.size();
if(n == 0) return 0;
int max_price = prices[n - 1];
int max_profit = 0;
for(int i = n - 2;i >= 0;i--)
{
max_profit = max(max_profit, max_price - prices[i]);
max_price = max(max_price,prices[i]);
}
return max_profit;
}
};
40 milli secs.
从其它地方查到一些别的思路,虽然并没有更好的复杂度,不过也可以当做新思路看看:
1)分治
最大差要么在左半边,要么在右半边,要么就是右半边最大值减左半边最小值;
2)b[i]=a[i+1]-a[i];
那么sum(b[i],b[j])=a[j+1]-a[i]; (j>=i)
最大差转化为最大连续子序列和问题
3) 设dp[i]为 max(dp[j]-dp[i]) j=i+1,i+2,...n-1
那么dp[i-1]=max(0,dp[i]+a[i]-a[i-1]),