接上一篇找零兑换问题的递归解法,找零兑换的动态规划算法:
从一分钱兑换开始,逐步建立一个兑换表:
11分钱的兑换法步骤如下:
def dpMakeChange(coinValueList, change, minCoins):
# 从1分开始到change逐个计算最少硬币数
for cents in range(1, change + 1):
# 1. 初始化一个最大值
coinCount = cents
# 2. 减去每个硬币,向后查最少硬币数
for j in [c for c in coinValueList if c <= cents]:
if minCoins[cents - j] + 1 < coinCount:
coinCount = minCoins[cents - j] + 1
# 3. 得到当前最少硬币数,记录到表中
minCoins[cents] = coinCount
# 返回最后一个结果
return minCoins[change]
print(dpMakeChange([1, 5, 10, 21, 25], 11, [0] * 12))
print(dpMakeChange([1, 5, 10, 21, 25], 63, [0] * 64))
运行代码可以得到找零11和63(贪心策略失效)的结果为2,3
注意:dpMakeChange并不是递归函数,是从递归算法出发得到的更高效算法
动态规划中最主要的思想是:
从最简单情况开始到达所需找零的循环其每一步都依靠以前的最优解来得到本步骤的最优解,直到得到答案。
扩展算法的目的是返回最优解的硬币组合:
def dpMakeChange(coinValueList, change, minCoins, coinsUsed):
# 从1分开始到change逐个计算最少硬币数
for cents in range(1, change + 1):
# 1. 初始化一个最大值
coinCount = cents
# 2. 初始化一下新加硬币
newCoin = 1
# 3. 减去每个硬币,向后查最少硬币数
for j in [c for c in coinValueList if c <= cents]:
if minCoins[cents - j] + 1 < coinCount:
coinCount = minCoins[cents - j] + 1
newCoin = j # 对应最小数量 所减的硬币
# 4. 得到当前最少硬币数,记录到表中
minCoins[cents] = coinCount
coinsUsed[cents] = newCoin
# 返回最后一个结果
return minCoins[change]
def printCoins(coinsUsed, change):
coin = change
while coin > 0:
thisCoin = coinsUsed[coin]
print(thisCoin)
coin = coin - thisCoin
amnt = 63
clist = [1, 5, 10, 21, 25]
coinsUsed = [0] * (amnt + 1)
coinCount = [0] * (amnt + 1)
print("Making change for", amnt, "requires")
print(dpMakeChange(clist, amnt, coinCount, coinsUsed), "coins")
print("They are:")
printCoins(coinsUsed, amnt)
print("The used list is as follows:")
print(coinsUsed)
运行结果如下:
原文:https://www.cnblogs.com/ikventure/p/14860866.html