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  • 0x0 题目详情
  • 0x1 解题思路
  • 0x2 代码实现
  • 0x3 课后总结

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  1. dynamic-programming

322-Coin-Change

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Last updated 4 years ago

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0x0 题目详情

给定不同面额的硬币 coins 和一个总金额 amount。编写一个函数来计算可以凑成总金额所需的最少的硬币个数。如果没有任何一种硬币组合能组成总金额,返回 -1。

测试用例:

示例 1: 输入: coins = [1, 2, 5], amount = 11 输出: 3 解释: 11 = 5 + 5 + 1

示例 2: 输入: coins = [2], amount = 3 输出: -1

说明: 你可以认为每种硬币的数量是无限的。

0x1 解题思路

思路一:

这道题暴力非常简单,对于一种面值的硬币,我们有三种选择:

  • 不使用该面值

  • 使用该面值的硬币一次

  • 使用该面值的硬币多次

那么当我们的余额为0时就表示已经无需计算了。暴力递归思路简单,但时间爆炸。按照这样的思路改成dp时间还是爆炸。

思路二:

采用贪心加递归的思路。既然要求最少的硬币数,那么我们就从最大的硬币开始找零,这个应该很容易懂。当然还需要剪枝,剪枝思路看实现代码。

0x2 代码实现

递归实现的代码比较简单了,这里就不写了。

贪心:递归函数的输入参数count的含义是,对于前面已经成功找零的余额选择了count个硬币。在递归函数中会更新最终结果res,所以无返回值。

class Solution {
    int res = Integer.MAX_VALUE;
    public int coinChange(int[] coins, int amount){
        if(amount==0){
            return 0;
            }
        Arrays.sort(coins);
        mincoin(coins,amount,coins.length-1,0);
        return res==Integer.MAX_VALUE? -1:res;
    }
    private void mincoin(int[] coins,int amount, int index, int count){
        if(amount==0){
            res = Math.min(res,count);
            return;
        }
        if(index<0){
            return;
        }
        for(int i = amount/coins[index];i>=0 && i+count<res; i--){
            mincoin(coins,amount - (i*coins[index]), index-1, count+i);
        }
    }
}

0x3 课后总结

不看答案我能做出来?

原题链接