给你一个整数数组coins
,表示不同面额的硬币;以及一个整数amount
,表示总金额。
计算并返回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
。
你可以认为每种硬币的数量是无限的。
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
示例 3:
输入:coins = [1], amount = 0
输出:0
示例 4:
输入:coins = [1], amount = 1
输出:1
示例 5:
输入:coins = [1], amount = 2
输出:2
提示:
- 1 <= coins.length <= 12
- 1 <= coins[i] <= 2^31 – 1
- 0 <= amount <= 10^4
1.dfs超时
Python:
class Solution:
def coinChange(self, coins: List[int], amount: int) -> int:
max_num = float('inf')
def backtrace(coins, amount, i, num):
nonlocal max_num
if amount > 0 and i < 0:
return
elif amount == 0 and i >= -1:
if num < max_num:
max_num = num
return
else:
if num > max_num:
return
for j in range(amount//coins[i], -1, -1):
if num+j >= max_num:
continue
backtrace(coins, amount-j*coins[i], i-1, num+j)
backtrace(coins, amount, len(coins)-1, 0)
return max_num if max_num != float('inf') else -1
2.动态规划
Python:
class Solution:
def coinChange(self, coins: List[int], amount: int) -> int:
dp = [-1 for i in range(amount+1)]
dp[0] = 0
for i in range(1, amount+1):
temp = [dp[i-j] for j in coins if i-j >= 0 and dp[i-j] != -1]
if temp:
dp[i] = min(temp) + 1
return dp[-1]
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