动态规划-Best Time to Buy and Sell Stock

题目
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.

Example 1:

Input: [7, 1, 5, 3, 6, 4]
Output: 5

max. difference = 6-1 = 5 (not 7-1 = 6, as selling price needs to be larger than buying price)
Example 2:

Input: [7, 6, 4, 3, 1]
Output: 0

In this case, no transaction is done, i.e. max profit = 0.
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题意解读:给定一个数组,数组的第i个元素是第i天的股票价格。如果你只允许进行一次买卖操作(买和买当做一次交易),设计一个算法寻找最大额收益
//d[i]代表[0,i]内交易股票的最大收益 minPrice表示[0,i)之间价格的最小值
//状态转移方程 dp[i] = max(dp[i-1],prices[i]-minPrice)

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作者:遇见更好的自己 
来源:CSDN 
原文:https://blog.csdn.net/yc1203968305/article/details/78173302 
版权声明:本文为博主原创文章,转载请附上博文链接!

暴力解法
public class MSB {
    public static void main(String args[]){
        int nums[]=new int[]{7,1,5,3,6,4};   //测试边界
        Solution test1=new Solution();
        System.out.println(test1.maxProfit(nums));
    }
}
class Solution {
    public int maxProfit(int[] prices) {
        int maxpfofit=0;
        for(int i=0;i<prices.length-1;i++){
            for(int  j=i+1;j<prices.length;j++){
                if(prices[j]>prices[i]){
                    maxpfofit=Math.max(maxpfofit,prices[j]-prices[i]);
                }
            }
        }
        return maxpfofit;
    }
}

动态规划

class Solution {
    public int maxProfit(int[] prices) {
        if(prices.length<2){
            return 0;
        }else{
            int minprice=prices[0];
            int res=0;
            for(int i=1;i<prices.length;i++){
                if(prices[i]>minprice){
                    res=Math.max(res,prices[i]-minprice);
                }else{
                    minprice=prices[i];
                }
            }
            if(res<=0){
                return 0;
            }else{
                return res;
            }
        }
    }
}

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转载自blog.csdn.net/anhuibozhoushatu/article/details/83579170